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Deep Learning Publications
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Deep Learning in Science P. Baldi.
Neural Network Gradient Hamiltonian Monte Carlo Li, L., Holbrook, A.J., Shahbaba, B., Baldi, P. Computational Statistics.
Improved energy reconstruction in NOvA with regression convolutional neural network Baldi, P., Bian, J., Hertel, L., et al. Physical Review D.
First measurement of neutrino oscillation parameters using neutrinos and antineutrinos by NOvA Acero, M.A., et al. Physical Review Letters.
Solving the Rubik’s cube with deep reinforcement learning and search Agostinelli, F., McAleer, S., Shmakov, A.K., Baldi, P. Nature Machine Intelligence.
Neuronal Capacity Baldi, P., Vershynin, R. Journal of Statistical Mechanics, Theory and Experiment.
Polynomial threshold functions, hyperplane arrangements, and random tensors Baldi, P., Vershynin, R. SIAM Journal of Mathematics of Data Science.
The capacity of feedforward neural networks Baldi, P., Vershynin, R. Neural Networks.
Deep Learning in the Natural Sciences: Applications to Physics. Sadowski, P., Baldi, P. Key Ideas in Learning Theory from Inception to Current State: Emmanuel Braverman's Legacy.
From Reinforcement Learning to Deep Reinforcement Learning: An Overview. Agostinelli, F., Hocquet, G., Singh, S., Baldi, P. Key Ideas in Learning Theory from Inception to Current State: Emmanuel Braverman's Legacy.
Deep Learning in Biomedical Data Science Baldi, P. Annual Review of Biomedical Data Science.
Development and Validation of a Deep Neural Network Model for Prediction of Postoperative In-Hospital Mortality Lee, C. K., Hofer, I., Gabel, E., Baldi, P., Cannesson, M. Anestgesiology.
Inner and Outer Recursive Neural Networks for Chemoinformatics Applications Urban, G., Subrahmanya, N., Baldi, P. Journal of Chemical Information and Modeling.
Deep learning convolutional neural networks accurately classify genetic mutation in gliomas Chang, P., Su, L., Baldi, P., Choi, D. American Journal of Neuroradiolog.
Learning in the Machine: Random Backpropagation and the Learning Channel Baldi, P., Sadowski, P., Lu, Z. Artifical Intelligence.
Longitudinal Monitoring of Biofilm Formation via Robust SERS Quantification of Pseudomonas aeruginosa-Produced Metabolite Nguyen, C., Thrift, W. J., Bhattacharjee, A., Ranjbar, S., Gallagher, T., Darvishzadeh-Varcheie, M., Sandersion, R., Capolimo, F., Whiteson, K., Baldi, P., Hochbaum, A., Ragan, R. ACS, Applied Materilas and Interfaces.
Learning in the Machine: Random Backpropagation and the Deep Learning Channel Baldi, P., Sadowski, P., Lu, Z. Artificial Intelligence.
CircadiOmics: Circadian Omic Data Web Portal Ceglia, N., Liu, Y., Chen, S., Agostinelli, F., Eckel-Mahan, K, Sassone-Corsi, P., Baldi, P. Nuclei Acids Research.
Deep Learning for Drug Discovery and Cancer Research: Automated Analysis of Vascularization Images Urban, G., Bache, K., Phan, D.T.T., Sorbrino, A., Shmakov, A.K., Hachey, S.J., Hughes, C.W., Baldi, P. IEEE/ACM Transactions on Computational Biology and Bioinformatics.
Deep-Learning Convolutional Neural Networks Accurately Classify Genetic Mutations in Gliomas Chang, P., Grinband, J., Winberg, B.D., Bardis, M., Khy, M., Cadena, G., Su, M.-Y., Cha, S., Filippi, C.G., Bota, D., Baldi, P., Poisson, L.M., Jain, R., Chow, D. American Journal of Neuroradiology.
Deep Learning Localizes and Identifies Polyps in Real Time with 96% Accuracy in Screening Colonoscopy Urban, G., Tripathi, P., Alkayali, T., Mittal, M., Jalali, F., Karnes, W., Baldi, P. Gastroenterology,.
Highly-Accurate Machine Fault Diagnosis Using Deep Transfer Learning Shao, S., McAleer, S., Yan, R., Baldi, P. IEEE Transactions on Industrial Informatics.
Learning in the machine: Recirculation is random backpropagation Baldi, P., Sadowski, P. Neural Networks.
Deep Learning for Predicitng Postoperative Outcomes: AKI, Reintubation, and In-Hospital Mortality Lee, C., Hofer, I., Baldi, P., Cannesson, M. American Society of Anesthesiologists Conference.
Deep Learning in Prediciting in Hospital Mortality Lee, C., Hofer, I., Cannesson, M., Baldi, P. Society for Technology in Anesthesia.
A Multi-Resolution Approach to Spinal Metastasis Detection using Dep Siamese Neural Networks Wang, J., Fang, Z., Lang, N., Yuan, H., Su, M., Baldi, P. Computers in Biology and Medicine.
Detecting Cardiovascular Disease from Mammograms with Deep Learning Wang, J., Ding, H., Azamian, F., Zhou, B., Iribarren, C., Molloi, S., Baldi, P. IEEE Transactions onBiomedical Imaging.
Efficient Antihydrogen Detection in Antimater Physics by Deep Learning Sadowski, P., Radics, B., Ananya, A., Yamazaki, Y., Baldi, P. Journal of Physics Communications.
Mir-132/212 is Required for Maturation of Binocular Matching Orientation Prference and Depth Perception Mazziotti, R., Baroncelli, L., Ceglia, N., Chelini, G., Della Sala, G., Magnan, C., Napoli, D., Putugnano, E., Silingardi, D., Tola, J., Tognini, P., Baldi, P., Pizzorusso, T. Nature Communicaiton.
Mutation of neuron-specific chromatin remodeling subunit BAF53b: Rescue of plasticity and memory by manipulating actin remodeling Ciernial, A. V., Kramar, E. A., Matheos, D. P., Havekes, R., Hemstedt, T. J., Magnan, C., Sakata, K., Tran, A., Azzawi, S., Lopez, A., Dang, R., Wang, W., Trieu, B., Tong, J., Barrett, R. M., Post, R.J., Baldi, P., Abel, T., Lynch, G., Wood, M. A. Learning and Memory.
Learning in the Machine: the Symmetries of the Deep Learning Channel Baldi, P., Sadowski, P., Lu, Z. Neural Networks.
The Inner and Outer Approaches for the Design or Recursive Neural Networks Architctures Baldi, P. Data Mining and Knowledg Discovery.
Decorrelated Jet Substructure Tagging using Adversarial Neural Networks Shimmin, C., Sadowski, P., Baldi, P., Weik, E., Whiteson, D., Goul, E., Sogaard, A. Physical Review D.
Deep learning for chemical reaction prediction Fooshee, D., Mood, A., Gutman, E., Tavakoli, A., Urban, G., Liu, F., Huynh, N., Van Vranken, D., Baldi, P. Molecular Systems Design & Engineering.
A Theory of Local Learning, the Learning Channel, and the Optimality of Backpropagation Baldi, P., Sadowski, P. Neural Networks.
What Time is it? Deep Learning Approaches for Circadian Rhythms Agostinelli, F., Ceglia, N., Shahbaba, B., Sassone-Corsi, P., Baldi, P. Bioinformatics.
Jet Substructure Classification in High-Energy Physics with Deep Neural Networks Baldi, P., Bauer, K., Eng, C., Sadowski, P., Whiteson, D. Physical Review D.
Parameterized Neural Networks for High-Energy Physics Baldi, P., Cranmer, K., Faucett, T., Sadowski, P., Whiteson, D. The European Physical Journal C.
VIRALpro: a tool to identify viral capsid and tail sequences Galiez, C., Magnan, C., Coste, F., Baldi, P. Bioinformatics.
Jet Flavor Classification in High-Energy Physics with Deep Neural Networks Guest, D., Collado, J., Baldi, P., Whiteson, D. Physical Review D.
Synergies Between Quantum Mechanics and Machine Learning in Reaction Prediction Sadowski, P., Fooshee, D., Subrahmanya, N., Baldi, P. Journal of Chemical Information and Modeling.
Enhanced Higgs to tau+tau- Search with Deep Learning P. Baldi, P. Sadowski, D. Whiteson. Physical Review Letters.
Mitochondrial Mutations in Subjects with Psychiatric Disorders Sequeira, A., Rollins, B., Magnan, C., van Oven, M., Baldi, P., Myers, R. M., Barchas, J. David, Schatzberg, A. F., Watson, S. J., Akil, H., Bunney, W. E., Vawter, M. P. PLOS ONE.
Deep Learning, Dark Knowledge, and Dark Matter Sadowski, P., Collado, J., Whiteson, D., Baldi, P. Journal of Machine Learning Research.
The Pervasiveness and Plasticity of Circadian Oscillations: The Coupled Circadian-Oscillators Framework Patel, V., Ceglia, N., Zeller, M., Eckel-Mahan, K., Sassone-Corsi, P., Baldi, P. Bioinformatics.
Accurate and Efficient Target Prediction Using a Potency-Sensitive Influence-Relevance Voter Lusci, A., Browning, M., Fooshee, D., Swamidass, S. Josh, Baldi, P. Journal of Cheminformatics.
Deep Autoencoder Neural Networks for Gene Ontology Annotation Predictions D. Chicco, P. Sadowski, P. Baldi. 5th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics.
Searching for Higgs Boson Decay Modes with Deep Learning P. Sadowski, D. Whiteson, P. Baldi. NIPS.
The Dropout Learning Algorithm P. Baldi, P. Sadowski. Artifical Intelligence.
Incorporating Post-Translational Modifications and Unnatural Amino Acids into High-Throughput Modeling of Protein Structures K. Nagata, A. Randall, P. Baldi. Bioinformatics.
Sspro/ACCpro 5.0: Almost Perfect Prediction of Protein Secondary Structure and Relative Solvent Accessibility. Problem Solved? C. Magnan, P. Baldi. Bioinformatics.
Deep Learning in High-Energy Physics: Improving the Search for Exotic Particles P. Baldi, P. Sadowski, D. Whiteson. Nature Communicaiton.
Enhanced Higgs to Tau-plus Tau-minus Search with Deep Learning Baldi, P., Sadowski, P., Whiteson, D. Pyhsical Review letters.
Deep Autoencoder Neural Networks for Gene Ontology Annotation Predictions Chicco, D., Sadowski, P., Baldi, P. IEEE/ACM Transactions on Computational Biology and Bioinformatics.
A Large-Scale Deep Learning Target-Prediction System for Diverse Molecules Lusci, A., Browning, M., Swamidass, S. Josh, Baldi, P. Journal of Chemical Information and Modeling.
The Pervasiveness and Plasticity of Circadian Oscillations Patel, V., Ceglia, N., Zeller, M., Eckel-Mahan, K., Sassone-Corsi, P., Baldi, P. Bioinformatics.
Understanding Dropout P. Sadowski, P. Baldi. NIPS.
Beyond Gradient Diffusion: New Algorithms for Training Deep Layers of Neural Networks J. Yarkony, P. Sadowski, B.S. Manjunath, P. Baldi. NIPS.
Deep Architectures and Deep Learning in Chemoinformatics: the Prediction of Aqueous Solubility for Drug-Like Molecules A. Lusci, G. Pollastri, P. Baldi. Journal of Chemical Information and Modeling.
Small-molecule 3D Structure Prediction Using Open Crystallography Data P. Sadowski, P. Baldi. Journal of Chemical Information and Modeling.
Neuron-Specific Nucleosome Remodeling Component BAF53b is Neccessary for Synaptic Plasticity and Memory Vogel-Ciernia, A, Matheos, D. P., Barrett, R. M., Kramar, E., Chen, Y., Magnan, C., Zeller, M., Sylvain, A., Azzawi, S., Haettig, J., Tran, A., Post, R.J., Crabtree, G. R., Baram, T. Z., Baldi, P., Lynch, G., Wood, M. A. Nature Neuroscience.
Deep Architectures and Learning for Protein Structure Prediction P. Di Lena, K. Nagata, P. Baldi. NIPS.
Deep Spatial-Temporal Architectures and Learning for Protein Structure Prediction P. Di Lena, K. Nagata, P. Baldi. NIPS.
Mitochondrial Mutations and Polymorphisms in Psychiatric Disorders. A. Sequeira, M. V. Martin, B. Rollins, E. A. Moon, W. E. Bunney, F. Macciardi, S. Lupoli, E. Smith, J. Kelsoe, C. Magnan, M. van Oven, P. Baldi, D.C. Wallace, M. P. Vawter. Frontiers in Behavioral and Psychiatric Genetics.
SIDEpro: a Novel Machine Learning Approach for the Fast and Accurate Prediction of Side-Chain Conformations. K. Nagata, A. Randall, P. Baldi. Protein: Structure, Function, and Bioinformaics.
Cyber-T Webserver: Differential Analysis of High-Throughput Data. M. Kayala, P. Baldi. Nucleic Acids Research.
Complex-Valued Autoencoders. P. Baldi, Z. Lu. Neural Networks.
Boolean autoencoders and hypercube clustering complexity Baldi, P. Designs, Codes and Cryptography.
Autoencoders, Unsupervised Learning, and Deep Architectures. Baldi, P. Journal of Machine Learning Research.
CircadiOmics: integrating circadian genomics, transcriptomics, proteomics and metabolomics. Patel, Vishal R., Eckel-Mahan, Kristin, Sassone-Corsi, Paolo, Baldi, Pierre. Nature methods.
ReactionPredictor: Prediction of Complex Chemical Reactions at the Mechanistic Level Using Machine Learning Kayala, Matthew A., Baldi, Pierre. Journal of Chemical Information and Modeling.
Deep architectures for protein contact map prediction Di Lena, Pietro, Nagata, Ken, Baldi, Pierre. Bioinformatics (Oxford, England).
A Machine Learning Approach to Predict Chemical Reactions. M. Kayla, P. Baldi. Neural Information Processing Systems 2011 (NIPS 2011).
SIDEpro: a Novel Machine Learning Approach for the Fast and Accurate Prediction of Side-Chain Conformations K. Nagata, A. Randall, P. Baldi. Protein: Structure, Function, and Bioinformaics.
Learning to Predict Chemical Reactions M. Kayala, C. Azencott, J. Chen, P. Baldi. Journal of Chemical Information and Modeling.
Visual Adaptation and Novelty Responses in the Superior Colliculus. S. Boehnke, D. Berg, R. Marino, P. Baldi, L. Itti, D. Munoz. European Journal of Neuroscience.
Autoencoders, Unsupervised Learning, and Deep Architectures. Baldi, P. Journal of Machine Learning Research.
Data-driven High-throughput Prediction of the 3-D Structure of Small Molecules: Review and Progress. Andronico, Alessio, Randall, Arlo, Benz, Ryan W., Baldi, Pierre. Journal of Chemical Information and Modeling.
Data-driven High-throughput Prediction of the 3-D Structure of Small Molecules: Review and Progress. Andronico, Alessio, Randall, Arlo, Benz, Ryan W., Baldi, Pierre. Journal of Chemical Information and Modeling.
Data-driven High-throughput Prediction of the 3-D Structure of Small Molecules: Review and Progress. Andronico, Alessio, Randall, Arlo, Benz, Ryan W., Baldi, Pierre. Journal of Chemical Information and Modeling.
Transmembrane β-Barrel Protein Structure Prediction. A. Randall, P. Baldi. Structural Bioinformatics of Membrane Proteins.
Reaction Explorer: Towards a Knowledge Map of Organic Chemistry to Support Dynamic Assessment and Personalized Instruction J. Chen, M. A. Kayala, P. Baldi. Enhancing Learning with Online Resources, Social Networking and Digital Libraries.
Autoencoders, Unsupervised Learning, and Deep Architectures. P. Baldi. Workshop on Deep Learning and Unsupervised Feature Learning.
Information-Theoretic Metrics for Project-Level Scattering and Tangling. E. Linstead, L. Hughes, C. Lopes, P. Baldi. International Conference on Software Engineering and Knowledge Engineering (SEKE).
Bridging the Gap Between Neural Network and Kernel Methods: Applications to Drug Discovery. P. Baldi, C. Azencott, S. J. Swamidass. WIRN 2010.
High-throughput Prediction of Protein Antigenicity Using Protein Microarray Data. Magnan, Christophe N., Zeller, Michael, Kayala, Matthew A., Vigil, Adam, Randall, Arlo, Felgner, Philip L., Baldi, Pierre. Bioinformatics (Oxford, England).
A CROC Stronger than ROC: Measuring, Visualizing, and Optimizing Early Retrieval. S. J. Swamidass, C. Azencott, K. Daily, P. Baldi. Bioinformatics.
Of Bits and Wows: A Bayesian Theory of Surprise with Applications to Attention. P. Baldi, L. Itti. Neural Networks.
When is Chemical Similarity Significant? The Statistical Distribution of Chemical Similarity Scores and Its Extreme Values. P. Baldi, R. Nasr. Journal of Chemical Information and Modeling.
Exploring Java Software Vocabulary: A Search and Mining Perspective. E. Linstead, L. Hughes, C. Lopes, P. Baldi. SUITE 2009: Proceedings of the First International Workshop on Search-Driven Development - Users, Tools, and Applications.
Software Analysis with Unsupervised Topic Models. E. Linstead, L. Hughes, C. Lopes, P. Baldi. Neural Information Processing Systems (NIPS) Conference.
The Evolution of Concerns, Scattering, and Tangling in Eclipse and ArgoUML. E. Linstead, L. Hughes, P. Baldi. Third International Symposium on Empirical Software Engineering and Measurement (ESEM).
Mining the Coherence of GNOME Bug Reports with Statistical Topic Models. E. Linstead, P. Baldi. MSR '09: Proceedings of the Sixth International Working Conference on Mining Software Repositories.
MotifMap: a human genome-wide map of candidate regulatory motif sites. X. Xie, P. Rigor, P. Baldi. Bioinformatics.
COBEpro: A Novel System for Predicting Continuous B-cell Epitopes. M. J. Sweredoski, P. Baldi. Protein Engineering Design and Selection.
Sourcerer: Mining and Searching Internet-Scale Software Repositories. E. Linstead, S. Bajracharya, T. Ngo, P. Rigor, C. Lopes, P. Baldi. Journal of Datamining and Knowledge Discovery.
The Influence Relevance Voter: An Accurate and Interpretable Virtual High Throughput Screening Method. S. J. Swamidass, C. Azencott, H. Gramajo, S. Tsai, P. Baldi. Journal of Chemical Information and Modeling.
SOLpro: Accurate Sequence-Based Prediction of Protein Solubility. C. N. Magnan, A. Randall, P. Baldi. Bioinformatics.
Bayesian Surprise Attracts Human Attention. L. Itti, P. Baldi. Vision Research.
A Theory of Aspects as Latent Topics. P. Baldi, C. Lopes, E. Linstead, S. Bajracharya. 2008 ACM SIGPLAN Conference on Object-Oriented Programming Systems, Languages, and Applications.
An Application of Latent Dirichlet Allocation to Analyzing Software Evolution. E. Linstead, C. Lopes, P. Baldi. International Conference on Machine Learning and Applications (ICMLA).
SELECTpro: Effective Protein Model Selection Using a Structure-Based Energy Function Resistant to Blunders. A. Randall, P. Baldi. BMC Structural Biology.
Machine Learning Methods for Protein Structure Prediction. J. Cheng, A. N. Tegge, P. Baldi. IEEE Reviews in Biomedical Engineering.
BLASTing Small Molecules—Statistics and Extreme Statistics of Chemical Similarity Scores. P. Baldi, R. W. Benz. Bioinformatics.
PEPITO: Improved Discontinuous B-Cell Epitope Prediction Using Multiple Distance Thresholds and Half-Sphere Exposure. M. J. Sweredoski, P. Baldi. Bioinformatics.
Discovery of Power-Laws in Chemical Space. R. W. Benz, S. J. Swamidass, P. Baldi. Journal of Chemical Information and Modeling.
Learning to Play Go Using Recursive Neural Networks. L. Wu, P. Baldi. Neural Networks.
TMBpro: Secondary Structure, β-Contact, and Tertiary Structure Prediction of Transmembrane β-Barrel Proteins. A. Randall, J. Cheng, M. Sweredoski, P. Baldi. Bioinformatics.
Virtual High-Throughput Screening with Two-Dimensional Kernels. A. Azencott, P. Baldi. Hands-On Pattern Recognition. Challenges in Data Representation, Model Selection, and Performance Prediction.
Mining Eclipse Developer Contributions via Author-Topic Models. E. Linstead, P. Rigor, S. Bajracharya, C. Lopes, P. Baldi. Proceedings of the MSR 2007: International Workshop on Mining Software Repositories.
Mining Concepts from Code with Probabilistic Topic Models. E. Linstead, P. Rigor, S. Bajracharya, C. Lopes, P. Baldi. Proceedings of the 22nd IEEE/ACM International Conference on Automated Software Engineering.
Mining Internet-Scale Software Repositories. E. Linstead, P. Rigor, S. Bajracharya, C. Lopes, P. Baldi. Advances in Neural Information Processing Systems 20.
One- to Four-Dimensional Kernels for Virtual Screening and the Prediction of Physical, Chemical, and Biological Properties. C. Azencott, A. Ksikes, S. Joshua Swamidass, J. Chen, L. Ralaivola, P. Baldi. Journal of Chemical Information and Modeling.
A bottom-up model of spatial attention predicts human error patterns in rapid scene recognition. W. Einhäuser, T. N. Mundhenk, P. Baldi, C. Koch, L. Itti. Journal of Vision.
Improved Residue Contact Prediction Using Support Vector Machines and a Large Feature Set. J. Cheng, P. Baldi. BMC Bioinformatics.
A Scalable Machine Learning Approach to Go. L. Wu, P. Baldi. Advances in Neural Information Processing Systems 19.
Functional Census of Mutation Sequence Spaces: The Example of p53 Cancer Rescue Mutants. S. A. Danziger, S. J. Swamidass, J. Zeng, L. R. Dearth, Q. Lu, J. H. Chen, J. Cheng, V. P. Hoang, H. Saigo, R. Luo, P. Baldi, Rainer K. Brachmann, Richard H. Lathrop. IEEE Transactions on Computational Biology and Bioinformatics.
Large-Scale Prediction of Disulphide Bridges Using Kernel Methods, Two-Dimensional Recursive Neural Networks, and Weighted Graph Matching. J. Cheng, H. Saigo, P. Baldi. Proteins.
Prediction of Protein Stability Changes for Single Site Mutations Using Support Vector Machines. J. Cheng, A. Randall, P. Baldi. Proteins.
DOMpro: Protein Domain Prediction Using Profiles, Secondary Structure, Relative Solvent Accessibility, and Recursive Neural Networks. J. Cheng, M. J. Sweredoski, P. Baldi. Data Mining and Knowledge Discovery.
Modular DAG-RNN Architectures for Assembling Coarse Protein Structures. G. Pollastri, A. Vullo, P. Frasconi, P. Baldi. Journal of Computational Biology.
A Machine Learning Information Retrieval Approach to Protein Fold Recognition. J. Cheng, P. Baldi. Bioinformatics.
Surprise: A Shortcut for Attention? P. Baldi. Neurobiology of Attention.
SVM and Pattern-Enriched Common Fate Graphs for the Game of GO. L. Ralaivola, L. Wu, P. Baldi. European Symposium on Artificial Neural Networks (ESANN).
A Principled Approach to Detecting Surprising Events in Video. L. Itti, P. Baldi. Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
Kernels for Small Molecules and the Prediction of Mutagenicity, Toxicity, and Anti-Cancer Activity. S. Swamidass, J. Chen, P. Phung, J. Bruand, L. Ralaivola, P. Baldi. 2005 Conference on Intelligent Systems for Molecular Biology (ISMB 05).
Three-Stage Prediction of Protein β-Sheets by Neural Networks, Alignments, and Graph Algorithms. J. Cheng, P. Baldi. 2005 Conference on Intelligent Systems for Molecular Biology (ISMB 05).
Bayesian Surprise Attracts Human Attention. L. Itti, P. Baldi. Advances in Neural Information Processing Systems 18, NIPS 2005.
Attention: Bits versus Wows. P. Baldi, L. Itti. Proceedings of the International Conference on Neural Networks and Brain.
Exploring Chemical Space with Computers: Informatics Challenges for AI and Machine Learning. P. Baldi. BIOMAT V Symposium.
Kernels for Small Molecules and the Prediction of Mutagenicity, Toxicity, and Anti-Cancer Activity. S. J. Swamidass, J. Chen, P. Phung, J. Bruand, L. Ralaivola, P. Baldi. Bioinformatics.
Three-Stage Prediction of Protein β-Sheets by Neural Networks, Alignments, and Graph Algorithms. J. Cheng, P. Baldi. Bioinformatics.
Polymodal sensory function of the C. elegans OCR-2 channel arises from distinct intrinsic determinants within the protein and is selectively conserved in human TRPV2. I. Sokolchik, T. Tanabe, P. Baldi, J. Y. Sze. Journal of Neuroscience.
Graph Kernels for Chemical Informatics. L. Ralaivola, J. S. Swamidass, H. Saigo, P. Baldi. Neural Networks.
On the Relationship Between Deterministic and Probabilistic Directed Graphical Models: from Bayesian Networks to Recursive Neural Networks. P. Baldi, M. Rosen-Zvi. Neural Networks.
SCRATCH: a Protein Structure and Structural Feature Prediction Server. J. Cheng, A. Z. Randall, M. Sweredoski, P. Baldi. Nucleic Acids Research.
Accurate Prediction of Protein Disordered Regions by Mining Protein Structure Data. J. Cheng, M. J. Sweredoski, P. Baldi. Data Mining and Knowledge Discovery.
Hidden Markov Models and Neural Networks. S. Kremer, P. Baldi. Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics.
Large-Scale Prediction of Disulphide Bond Connectivity. P. Baldi, J. Cheng, A. Vullo. Advances in Neural Information Processing Systems 17 (NIPS 2004).
New Machine Learning Methods for the Prediction of Protein Topologies. P. Baldi, G. Pollastri, P. Frasconi, A. Vullo. Artificial Intelligence and Heuristic Methods in Bioinformatics.
Modeling the Internet and the Web: Probabilistic Methods and Algorithms. P. Baldi, P. Frasconi, P. Smyth.
Prediction of Protein Topologies Using Generalized IOHMMs and RNNs. G. Pollastri, P. Baldi, A. Vullo, P. Frasconi. Advances in Neural Information Processing Systems 15.
Combining Protein Secondary Structure Prediction Models With Ensemble Methods of Optimal Complexity. Y. Guermeur, G. Pollastri, A. Elisseeff, D. Zelus, H. Paugam-Moisy, P. Baldi. Neurocomputing.
The Principled Design of Large-Scale Recursive Neural Network Architectures—DAG-RNNs and the Protein Structure Prediction Problem. P. Baldi, G. Pollastri. Journal of Machine Learning Research.
A Computational Theory of Surprise. P. Baldi. Information, Coding, and Mathematics.
Prediction of Contact Maps by GIOHMMs and Recurrent Neural Networks Using Lateral Propagation From All Four Cardinal Corners. G. Pollastri, P. Baldi. Proceedings of the 2002 Conference on Intelligent Systems for Molecular Biology (ISMB 02).
Prediction of Contact Maps by GIOHMMs and Recurrent Neural Networks Using Lateral Propagation From All Four Cardinal Corners. G. Pollastri, P. Baldi. Bioinformatics.
Improving the Prediction of Protein Secondary Structure in Three and Eight Classes Using Recurrent Neural Networks and Profiles. G. Pollastri, D. Przybylski, B. Rost, P. Baldi. Proteins.
Prediction of Coordination Number and Relative Solvent Accessibility in Proteins. G. Pollastri, P. Baldi, P. Fariselli, R. Casadio. Proteins.
A Machine Learning Strategy for Protein Analysis. P. Baldi, G. Pollastri. IEEE Intelligent Systems (special Issue on "Intelligent Systems in Biology").
Modeling and Optimization of UWB Communication Networks Through a Flexible Cost Function. P. Baldi, L. De Nardis, M. G. Di Benedetto. IEEE Journal on Selected Areas in Communications.
A Model for Self-Organizing Large Scale Wireless Networks. M. Di Benedetto, P. Baldi. International Symposium on 3G Infrastructure and Services.
Improved Prediction of the Number of Residue Contacts in Proteins by Recurrent Neural Networks. G. Pollastri, P. Baldi, P. Fariselli, R. Casadio. Proceedings of the 2001 Conference on Intelligent Systems for Molecular Biology, (ISMB01).
Improved Prediction of the Number of Residue Contacts in Proteins by Recurrent Neural Networks. G. Pollastri, P. Baldi, P. Fariselli, R. Casadio. Bioinformatics.
A Bayesian Framework for the Analysis of Microarray Expression Data: Regularized t-Test and Inference of Gene Changes. P. Baldi, A. D. Long. Bioinformatics.
Bidirectional IOHMMs and recurrent neural networks for protein secondary structure prediction. P. Baldi, S. Brunak, G. Pollastri, P. Frasconi. Protein Sequence Analysis in the Genomic Era.
Bidirectional Dynamics for Protein Secondary Structure Prediction. P. Baldi, S. Brunak, P. Frasconi, G. Pollastri, G. Soda. Sequence Learning: Paradigms, Algorithms, and Applications.
Protein β-Sheet Partner Prediction by Neural Networks. P. Baldi, G. Pollastri, C. A. F. Andersen, S. Brunak. Artifical Neural Networks in Medicine and Biology. Proceedings of the ANNIMAB-1 Conference.
Matching Protein β-Sheet Partners by Feedforward and Recurrent Neural Networks. P. Baldi, G. Pollastri, C. A. F. Andersen, S. Brunak. Proceedings of the 2000 Conference on Intelligent Systems for Molecular Biology (ISMB00).
Probabilistic Graphical Models in Computational Molecular Biology. P. Baldi. Journal of the Italian Association for Artificial Intelligence.
On the Convergence of a Clustering Algorithm for Protein-Coding Regions in Microbial Genomes. P. Baldi. Bioinformatics.
Assessing the Accuracy of Prediction Algorithms for Classification: An Overview. P. Baldi, S. Brunak, Y. Chauvin, H. Nielsen. Bioinformatics.
Exploiting the Past and the Future in Protein Secondary Structure Prediction. P. Baldi, S. Brunak, P. Frasconi, G. Soda, G. Pollastri. Bioinformatics.
Probabilistic Models of Neuronal Spike Trains. P. Baldi. Adaptive Processing of Temporal Information.
Software Foundation Libraries for the Design of Intelligent Systems. P. Baldi, Y. Chauvin, V. Mittal Henkle. Neural Nets WIRN Vietri 98. Proceedings of the 10-th Italian Workshop on Neural Nets.
Bioinformatics: the Machine Learning Approach. P. Baldi, S. Brunak.
On the Use of Bayesian Methods for Evaluating Compartmental Neural Models. P. Baldi, M. C. Vanier, J. M. Bower. Journal of Computational Neuroscience.
Universal Approximation and Learning of Trajectories Using Oscillators. P. Baldi, K. Hornik. Advances in Neural Information Processing Systems 8.
Hidden Markov Models for Human Genes: Periodic Patterns in Exon Sequences. P. Baldi, S. Brunak, Y. Chauvin, A. Krogh. Theoretical and Computational Methods in Genome Research.
Hybrid Modeling, HMM/NN Architectures, and Protein Applications. P. Baldi, Y. Chauvin. Neural Computation.
When Neural Networks Play Sherlock Holmes. P. Baldi, Y. Chauvin. Back-Propagation: Theory, Architectures and Applications.
Gradient Descent Learning Algorithms: A Unified Perspective. P. Baldi. Back-Propagation: Theory, Architectures and Applications.
Back-propagation and unsupervised learning in linear networks. P. Baldi, Y. Chauvin, K. Hornik. Back-Propagation: Theory, Architectures and Applications.
Inferring Ground Truth from Subjective Labelling of Venus Images. P. Smyth, U. Fayadd, P. Perona, M. Burl, P. Baldi. Advances in Neural Information Processing Systems.
Protein Modeling with Hybrid Hidden Markov Model/Neural Network Architectures. P. Baldi, Y. Chauvin. Proceedings of the 1995 Conference on Intelligent Systems for Molecular Biology (ISMB95).
Gradient Descent Learning Algorithms Overview: A General Dynamical Systems Perspective. P. Baldi. IEEE Transactions on Neural Networks.
Learning in Linear Networks: a Survey. P. Baldi, K. Hornik. IEEE Transactions on Neural Networks.
Substitution Matrices and Hidden Markov Models. P. Baldi. Journal of Computational Biology.
Statistical Models of Proteins: an Application to the G-Protein-Coupled Receptor Family. P. Baldi, Y. Chauvin. Modern Approaches in Molecular Bioinformatics.
Trading Decision Learning: from Theory to Personal Traders. P. Baldi, Y. Chauvin. Proceedings of the Second International Conference on Neural Networks in the Capital Markets.
Modeling Protein Families and Human Genes: Hidden Markov Models and a Little Beyond. P. Baldi, Y. Chauvin. Proceedings of the 1994 Fifth Generation Computing Symposium, Workshop on Fusion of Molecular Biology and Knowledge Processing.
Discrimination of Tyrosine and Serine/Threonine Kinase Sub-Families by Hidden Markov Models. P. Baldi, Y. Chauvin. Proceedings of The Third International Conference on Bioinformatics and Genome Research.
Hidden Markov Models of Human Genes. P. Baldi, S. Brunak, Y. Chauvin, J. Engelbrecht, A. Krogh. Advances in Neural Information Processing Systems.
How Delays Affect Neural Dynamics and Learning. P. Baldi, A. Atiya. IEEE Transactions on Neural Networks.
Smooth On-Line Learning Algorithms for Hidden Markov Models. P. Baldi, Y. Chauvin. Neural Computation.
Hidden Markov Models of Biological Primary Sequence Information. P. Baldi, Y. Chauvin, T. Hunkapiller, M. A. McClure. PNAS USA.
Hidden Markov Models of the G-Protein Coupled Receptor Family. P. Baldi, Y. Chauvin. Journal of Computational Biology.
Learning Trajectories with a Hierarchy of Oscillatory Modules. P. Baldi, Nikzad Toomarian. Proceedings of the 1993 IEEE International Conference on Neural Networks.
Hidden Markov Models in Molecular Biology: New Algorithms and Applications. P. Baldi, Y. Chauvin, T. Hunkapiller, M. A. McClure. Advances in Neural Information Processing Systems.
Random Interactions in Higher-Orders Neural Networks. P. Baldi, S.S. Venkatesh. IEEE Transactions on Information Theory.
Neural Networks for Fingerprint Recognition. P. Baldi, Y. Chauvin. Neural Computation.
A Modular Hierarchical Approach to Learning. P. Baldi. Proceedings of the 2nd International Conference on Fuzzy Logic and Neural Networks.
Trading Decision Learning. P. Baldi, Y. Chauvin. Neural Networks for Computing Conference (abstract).
Programmed Interactions in Higher-Orders Neural Networks: I. Maximal Capacity. S.S. Venkatesh, P. Baldi. Journal of Complexity.
Programmed Interactions in Higher-Orders Neural Networks: II. The Outer-Product Algorithm. S. S. Venkatesh, P. Baldi. Journal of Complexity.
Temporal Evolution of Generalization during Learning in Linear Networks. P. Baldi, Y. Chauvin. Neural Computation.
Contrastive Learning and Neural Oscillations. P. Baldi, F. Pineda. Neural Computation.
Computing with Arrays of Bell-Shaped and Sigmoid Functions. P. Baldi. Proceedings of the 1990 conference on Advances in neural information processing systems 3.
Computing with Arrays of Coupled Oscillators: an Application to Preattentive Texture Discrimination. P. Baldi, R. Meir. Neural Computation.
A Normal Approximation for the Number of Local Maxima of a Random Function on a Graph. P. Baldi, Y. Rinott, C. Stein. Probability, Statistics and Mathematics: Papers in Honor of Samuel Karlin.
On the Distribution of the Number of Local Minima of a Random Function on a Graph. P. Baldi, Y. Rinott, C. Stein. Proceedings of the 1989 Conference on Neural Information Processing Systems.
Asymptotic Normality of Some Graph Related Statistics. P. Baldi, Y. Rinott. Journal of Applied Probability.
On Normal Approximations of Distributions in Terms of Dependency Graphs. P. Baldi, Y. Rinott. Annals of Probability.
Oscillations and Synchronizations in Neural Networks: an Exploration of the Labeling Hypothesis. P. Baldi, A. Atiya. International Journal of Neural Systems.
Neural Networks and Principal Component Analysis. P. Baldi. Proceedings of the 1988 Conference on Neural Information Processing.
Neural Networks and Principal Component Analysis: Learning from Examples without Local Minima. P. Baldi, K. Hornik. Neural Networks.
Neural Networks, Orientations of the Hypercube and Algebraic Threshold Functions. P. Baldi. IEEE Transactions on Information Theory.
Group Actions and Learning for a Family of Automata. P. Baldi. Journal of Computer and System Sciences.
Neural Networks, Acyclic Orientations of the Hypercube and Sets of Orthogonal Vectors. P. Baldi. SIAM Journal of Discrete Mathematics.
How Sensory Maps Could Enhance Resolution Through Ordered Arrangements of Broadly Tuned Receivers. P. Baldi, W. Heiligenberg. Biological Cybernetics.
On Properties of Networks of Neuron-Like Elements: Complexity and Capacity. P. Baldi, S.S. Venkatesh. Proceedings of the IEEE Conference on Neural Information Processing Systems.
Number of Stable Points for Spin Glasses and Neural Networks of Higher Orders. P. Baldi, S.S. Venkatesh. Physical Review Letters.
Symmetries and Learning in Neural Network Models. P. Baldi. Physical Review Letters.
Embeddings of Ultrametric Spaces in Finite Dimensional Structures. M. Aschbacher, P. Baldi, E. B. Baum, R.M. Wilson. SIAM Journal of Algebraic and Discrete Methods.
Caging and Exhibiting Ultrametric Structures. P. Baldi, E.B. Baum. Proceedings of the Conference on Neural Networks for Computing.
Bounds on the Size of Ultrametric Structures. P. Baldi, E.B. Baum. Physical Review Letters.
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