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ORCIDPierre Baldi
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- affiliation: University of California, Irvine, CA, USA
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2020 – today
- 2023
[j145]Pierre Baldi
, Roman Vershynin:
The quarks of attention: Structure and capacity of neural attention building blocks. Artif. Intell. 319: 103901 (2023)- [j144]Mohammadamin Tavakoli, Yin Ting T. Chiu, Pierre Baldi, Ann Marie Carlton, David Van Vranken:
RMechDB: A Public Database of Elementary Radical Reaction Steps. J. Chem. Inf. Model. 63(4): 1114-1123 (2023) - [i46]Alexander Shmakov, Alejandro Yankelevich, Jianming Bian, Pierre Baldi:
Interpretable Joint Event-Particle Reconstruction for Neutrino Physics at NOvA with Sparse CNNs and Transformers. CoRR abs/2303.06201 (2023) - [i45]Geunwoo Kim, Pierre Baldi, Stephen McAleer:
Language Models can Solve Computer Tasks. CoRR abs/2303.17491 (2023) - [i44]Alexander Shmakov, Kevin Greif, Michael James Fenton, Aishik Ghosh, Pierre Baldi, Daniel Whiteson:
End-To-End Latent Variational Diffusion Models for Inverse Problems in High Energy Physics. CoRR abs/2305.10399 (2023) - [i43]Junze Liu, Aishik Ghosh, Dylan Smith, Pierre Baldi, Daniel Whiteson:
Generalizing to new calorimeter geometries with Geometry-Aware Autoregressive Models (GAAMs) for fast calorimeter simulation. CoRR abs/2305.11531 (2023) - 2022
- [j143]Gregor Urban, Christophe N. Magnan, Pierre Baldi:
SSpro/ACCpro 6: almost perfect prediction of protein secondary structure and relative solvent accessibility using profiles, deep learning and structural similarity. Bioinform. 38(7): 2064-2065 (2022) - [j142]Lars Hertel, Pierre Baldi, Daniel L. Gillen:
Reproducible Hyperparameter Optimization. J. Comput. Graph. Stat. 31(1): 84-99 (2022) - [j141]Pierre Baldi:
Call for a Public Open Database of All Chemical Reactions. J. Chem. Inf. Model. 62(9): 2011-2014 (2022) - [j140]Mohammadamin Tavakoli, Aaron Mood, David Van Vranken, Pierre Baldi:
Quantum Mechanics and Machine Learning Synergies: Graph Attention Neural Networks to Predict Chemical Reactivity. J. Chem. Inf. Model. 62(9): 2121-2132 (2022) - [j139]Siwei Chen, Gregor Urban, Pierre Baldi:
Weakly Supervised Polyp Segmentation in Colonoscopy Images Using Deep Neural Networks. J. Imaging 8(5): 121 (2022) - [j138]Muntaha Samad, Forest Agostinelli, Tomoki Sato, Kohei Shimaji, Pierre Baldi:
CircadiOmics: circadian omic web portal. Nucleic Acids Res. 50(W1): 183-190 (2022) - [i42]Mohammadamin Tavakoli, Alexander Shmakov, Francesco Ceccarelli, Pierre Baldi:
Rxn Hypergraph: a Hypergraph Attention Model for Chemical Reaction Representation. CoRR abs/2201.01196 (2022) - [i41]Stephen McAleer, Kevin Wang, John B. Lanier, Marc Lanctot, Pierre Baldi, Tuomas Sandholm, Roy Fox:
Anytime PSRO for Two-Player Zero-Sum Games. CoRR abs/2201.07700 (2022) - [i40]Pierre Baldi, Roman Vershynin:
The Quarks of Attention. CoRR abs/2202.08371 (2022) - [i39]Alexander Shmakov, Mohammadamin Tavakoli, Pierre Baldi, Christopher M. Karwin, Alex Broughton, Simona Murgia:
Deep Learning Models of the Discrete Component of the Galactic Interstellar Gamma-Ray Emission. CoRR abs/2206.02819 (2022) - [i38]Stephen McAleer, John B. Lanier, Kevin A. Wang, Pierre Baldi, Roy Fox, Tuomas Sandholm:
Self-Play PSRO: Toward Optimal Populations in Two-Player Zero-Sum Games. CoRR abs/2207.06541 (2022) - [i37]John B. Lanier, Stephen McAleer, Pierre Baldi, Roy Fox:
Feasible Adversarial Robust Reinforcement Learning for Underspecified Environments. CoRR abs/2207.09597 (2022) - [i36]Junze Liu, Aishik Ghosh, Dylan Smith, Pierre Baldi, Daniel Whiteson:
Geometry-aware Autoregressive Models for Calorimeter Shower Simulations. CoRR abs/2212.08233 (2022) - 2021
- [j137]Pietro Di Lena, Pierre Baldi:
Fold recognition by scoring protein maps using the congruence coefficient. Bioinform. 37(4): 506-513 (2021) - [j136]Mohammadamin Tavakoli, Forest Agostinelli, Pierre Baldi:
SPLASH: Learnable activation functions for improving accuracy and adversarial robustness. Neural Networks 140: 1-12 (2021) - [j135]Pierre Baldi, Roman Vershynin:
A theory of capacity and sparse neural encoding. Neural Networks 143: 12-27 (2021) - [j134]Christine K. Lee, Muntaha Samad, Ira Hofer, Maxime Cannesson, Pierre Baldi:
Development and validation of an interpretable neural network for prediction of postoperative in-hospital mortality. npj Digit. Medicine 4 (2021) - [c81]Yasaman Razeghi, Kalev Kask, Yadong Lu, Pierre Baldi, Sakshi Agarwal, Rina Dechter:
Deep Bucket Elimination. IJCAI 2021: 4235-4242 - [c80]Stephen McAleer, John B. Lanier, Kevin A. Wang, Pierre Baldi, Roy Fox:
XDO: A Double Oracle Algorithm for Extensive-Form Games. NeurIPS 2021: 23128-23139 - [c79]Farima Farmahinifarahani, Yadong Lu, Vaibhav Saini, Pierre Baldi, Cristina V. Lopes:
D-REX: Static Detection of Relevant Runtime Exceptions with Location Aware Transformer. SCAM 2021: 198-208 - [i35]Jordan Ott, David Bruyette, Cody L. Arbuckle, Dylan Balsz, Silke Hecht, Lisa Shubitz, Pierre Baldi:
Detecting Pulmonary Coccidioidomycosis (Valley fever) with Deep Convolutional Neural Networks. CoRR abs/2102.00280 (2021) - [i34]Forest Agostinelli, Alexander Shmakov, Stephen McAleer, Roy Fox, Pierre Baldi:
A* Search Without Expansions: Learning Heuristic Functions with Deep Q-Networks. CoRR abs/2102.04518 (2021) - [i33]Pierre Baldi, Roman Vershynin:
A theory of capacity and sparse neural encoding. CoRR abs/2102.10148 (2021) - [i32]Stephen McAleer, John B. Lanier, Pierre Baldi, Roy Fox:
XDO: A Double Oracle Algorithm for Extensive-Form Games. CoRR abs/2103.06426 (2021) - [i31]Mohammadamin Tavakoli, Aaron Mood, David Van Vranken, Pierre Baldi:
Quantum Mechanics and Machine Learning Synergies: Graph Attention Neural Networks to Predict Chemical Reactivity. CoRR abs/2103.14536 (2021) - [i30]Alexander Shmakov, Michael James Fenton, Ta-Wei Ho, Shih-Chieh Hsu, Daniel Whiteson, Pierre Baldi:
SPANet: Generalized Permutationless Set Assignment for Particle Physics using Symmetry Preserving Attention. CoRR abs/2106.03898 (2021) - [i29]Stephen McAleer, John B. Lanier, Michael Dennis, Pierre Baldi, Roy Fox:
Improving Social Welfare While Preserving Autonomy via a Pareto Mediator. CoRR abs/2106.03927 (2021) - [i28]Mohammadamin Tavakoli, Peter J. Sadowski, Pierre Baldi:
Tourbillon: a Physically Plausible Neural Architecture. CoRR abs/2107.06424 (2021) - 2020
- [j133]Jordan Ott, Erik Linstead, Nicholas LaHaye, Pierre Baldi:
Learning in the machine: To share or not to share? Neural Networks 126: 235-249 (2020) - [j132]Ira Hofer, Christine K. Lee, Eilon Gabel, Pierre Baldi, Maxime Cannesson:
Development and validation of a deep neural network model to predict postoperative mortality, acute kidney injury, and reintubation using a single feature set. npj Digit. Medicine 3 (2020) - [j131]Lars Hertel, Julian Collado, Peter J. Sadowski, Jordan Ott, Pierre Baldi:
Sherpa: Robust hyperparameter optimization for machine learning. SoftwareX 12: 100591 (2020) - [j130]Jordan Ott, Mike Pritchard, Natalie Best, Erik Linstead, Milan Curcic, Pierre Baldi:
A Fortran-Keras Deep Learning Bridge for Scientific Computing. Sci. Program. 2020: 8888811:1-8888811:13 (2020) - [c78]Mohammadamin Tavakoli, Pierre Baldi:
Continuous Representation of Molecules using Graph Variational Autoencoder. AAAI Spring Symposium: MLPS 2020 - [c77]Stephen McAleer, John B. Lanier, Roy Fox, Pierre Baldi:
Pipeline PSRO: A Scalable Approach for Finding Approximate Nash Equilibria in Large Games. NeurIPS 2020 - [i27]Mohammadamin Tavakoli, Pierre Baldi:
Continuous Representation of Molecules Using Graph Variational Autoencoder. CoRR abs/2004.08152 (2020) - [i26]Jordan Ott, Mike Pritchard, Natalie Best, Erik Linstead, Milan Curcic, Pierre Baldi:
A Fortran-Keras Deep Learning Bridge for Scientific Computing. CoRR abs/2004.10652 (2020) - [i25]Lars Hertel, Julian Collado, Peter J. Sadowski, Jordan Ott, Pierre Baldi:
Sherpa: Robust Hyperparameter Optimization for Machine Learning. CoRR abs/2005.04048 (2020) - [i24]Stephen McAleer, John B. Lanier, Roy Fox, Pierre Baldi:
Pipeline PSRO: A Scalable Approach for Finding Approximate Nash Equilibria in Large Games. CoRR abs/2006.08555 (2020) - [i23]Mohammadamin Tavakoli, Forest Agostinelli, Pierre Baldi:
SPLASH: Learnable Activation Functions for Improving Accuracy and Adversarial Robustness. CoRR abs/2006.08947 (2020) - [i22]Lars Hertel, Pierre Baldi, Daniel L. Gillen:
Quantity vs. Quality: On Hyperparameter Optimization for Deep Reinforcement Learning. CoRR abs/2007.14604 (2020) - [i21]Michael James Fenton, Alexander Shmakov, Ta-Wei Ho, Shih-Chieh Hsu, Daniel Whiteson, Pierre Baldi:
Permutationless Many-Jet Event Reconstruction with Symmetry Preserving Attention Networks. CoRR abs/2010.09206 (2020) - [i20]Stephen McAleer, Alex Fast, Yuntian Xue, Magdalene Seiler, William Tang, Mihaela Balu, Pierre Baldi, Andrew W. Browne:
Deep machine learning-assisted multiphoton microscopy to reduce light exposure and expedite imaging. CoRR abs/2011.06408 (2020) - [i19]Junze Liu, Jordan Ott, Julian Collado, Benjamin Jargowsky, Wenjie Wu, Jianming Bian, Pierre Baldi:
Deep-Learning-Based Kinematic Reconstruction for DUNE. CoRR abs/2012.06181 (2020)
2010 – 2019
- 2019
- [j129]Lingge Li, Andrew Holbrook, Babak Shahbaba, Pierre Baldi:
Neural network gradient Hamiltonian Monte Carlo. Comput. Stat. 34(1): 281-299 (2019) - [j128]Forest Agostinelli, Stephen McAleer, Alexander Shmakov, Pierre Baldi:
Solving the Rubik's cube with deep reinforcement learning and search. Nat. Mach. Intell. 1(8): 356-363 (2019) - [j127]Pierre Baldi, Roman Vershynin:
The capacity of feedforward neural networks. Neural Networks 116: 288-311 (2019) - [j126]Pierre Baldi, Roman Vershynin:
Polynomial Threshold Functions, Hyperplane Arrangements, and Random Tensors. SIAM J. Math. Data Sci. 1(4): 699-729 (2019) - [j125]Gregor Urban, Kevin Bache, Duc T. T. Phan, Agua Sobrino, Alexander Shmakov, Stephanie J. Hachey, Christopher C. W. Hughes, Pierre Baldi:
Deep Learning for Drug Discovery and Cancer Research: Automated Analysis of Vascularization Images. IEEE ACM Trans. Comput. Biol. Bioinform. 16(3): 1029-1035 (2019) - [j124]Siyu Shao, Stephen McAleer, Ruqiang Yan, Pierre Baldi:
Highly Accurate Machine Fault Diagnosis Using Deep Transfer Learning. IEEE Trans. Ind. Informatics 15(4): 2446-2455 (2019) - [c76]Lingge Li, Nitish Nayak, Jianming Bian, Pierre Baldi:
Efficient Neutrino Oscillation Parameter Inference with Gaussian Process. AAAI 2019: 9967-9968 - [c75]Stephen McAleer, Forest Agostinelli, Alexander Shmakov, Pierre Baldi:
Solving the Rubik's Cube with Approximate Policy Iteration. ICLR (Poster) 2019 - [c74]Vaibhav Saini, Farima Farmahinifarahani, Yadong Lu, Di Yang, Pedro Martins, Hitesh Sajnani, Pierre Baldi, Cristina V. Lopes:
Towards automating precision studies of clone detectors. ICSE 2019: 49-59 - [c73]Pierre Baldi, Peter J. Sadowski, Zhiqin Lu:
Learning in the Machine: Random Backpropagation and the Deep Learning Channel (Extended Abstract). IJCAI 2019: 6348-6352 - [c72]Lingge Li, Dustin S. Pluta, Babak Shahbaba, Norbert Fortin, Hernando Ombao, Pierre Baldi:
Modeling Dynamic Functional Connectivity with Latent Factor Gaussian Processes. NeurIPS 2019: 8261-8271 - [i18]Pierre Baldi, Roman Vershynin:
The capacity of feedforward neural networks. CoRR abs/1901.00434 (2019) - [i17]John B. Lanier, Stephen McAleer, Pierre Baldi:
Curiosity-Driven Multi-Criteria Hindsight Experience Replay. CoRR abs/1906.03710 (2019) - [i16]Jordan Ott, Erik Linstead, Nicholas LaHaye, Pierre Baldi:
Learning in the Machine: To Share or Not to Share? CoRR abs/1909.11483 (2019) - [i15]Alexander Shmakov, John B. Lanier, Stephen McAleer, Rohan Achar, Cristina V. Lopes, Pierre Baldi:
ColosseumRL: A Framework for Multiagent Reinforcement Learning in N-Player Games. CoRR abs/1912.04451 (2019) - 2018
- [j123]Pierre Baldi, Peter J. Sadowski, Zhiqin Lu:
Learning in the machine: Random backpropagation and the deep learning channel. Artif. Intell. 260: 1-35 (2018) - [j122]Pierre Baldi:
The inner and outer approaches to the design of recursive neural architectures. Data Min. Knowl. Discov. 32(1): 218-230 (2018) - [j121]Gregor Urban, Niranjan Subrahmanya, Pierre Baldi:
Inner and Outer Recursive Neural Networks for Chemoinformatics Applications. J. Chem. Inf. Model. 58(2): 207-211 (2018) - [j120]Clara H. Eng, Tyler W. H. Backman, Constance B. Bailey, Christophe N. Magnan, Héctor García Martín, Leonard Katz, Pierre Baldi, Jay D. Keasling:
ClusterCAD: a computational platform for type I modular polyketide synthase design. Nucleic Acids Res. 46(Database-Issue): D509-D515 (2018) - [j119]Nicholas Ceglia, Yu Liu, Siwei Chen, Forest Agostinelli, Kristin Eckel-Mahan, Paolo Sassone-Corsi, Pierre Baldi:
CircadiOmics: circadian omic web portal. Nucleic Acids Res. 46(Webserver-Issue): W157-W162 (2018) - [j118]Pierre Baldi, Peter J. Sadowski:
Learning in the machine: Recirculation is random backpropagation. Neural Networks 108: 479-494 (2018) - [c71]Pierre Baldi, Roman Vershynin:
On Neuronal Capacity. NeurIPS 2018: 7740-7749 - [c70]Vaibhav Saini, Farima Farmahinifarahani, Yadong Lu, Pierre Baldi, Cristina V. Lopes:
Oreo: detection of clones in the twilight zone. ESEC/SIGSOFT FSE 2018: 354-365 - [i14]Stephen McAleer, Forest Agostinelli, Alexander Shmakov, Pierre Baldi:
Solving the Rubik's Cube Without Human Knowledge. CoRR abs/1805.07470 (2018) - [i13]Vaibhav Saini, Farima Farmahinifarahani, Yadong Lu, Pierre Baldi, Cristina V. Lopes:
Oreo: Detection of Clones in the Twilight Zone. CoRR abs/1806.05837 (2018) - [i12]Vaibhav Saini, Farima Farmahinifarahani, Yadong Lu, Di Yang, Pedro Martins, Hitesh Sajnani, Pierre Baldi, Cristina V. Lopes:
Towards Automating Precision Studies of Clone Detectors. CoRR abs/1812.05195 (2018) - 2017
- [j117]Yu Liu, Sha Sun, Timothy Bredy, Marcelo A. Wood, Robert C. Spitale, Pierre Baldi:
MotifMap-RNA: a genome-wide map of RBP binding sites. Bioinform. 33(13): 2029-2031 (2017) - [j116]Juan Wang, Zhiyuan Fang, Ning Lang, Huishu Yuan, Min-Ying Su, Pierre Baldi:
A multi-resolution approach for spinal metastasis detection using deep Siamese neural networks. Comput. Biol. Medicine 84: 137-146 (2017) - [j115]Pierre Baldi, Peter J. Sadowski, Zhiqin Lu:
Learning in the machine: The symmetries of the deep learning channel. Neural Networks 95: 110-133 (2017) - [j114]Juan Wang, Huanjun Ding, Fatemeh Azamian Bidgoli, Brian Zhou, Carlos Iribarren, Sabee Molloi, Pierre Baldi:
Detecting Cardiovascular Disease from Mammograms With Deep Learning. IEEE Trans. Medical Imaging 36(5): 1172-1181 (2017) - [c69]Peter J. Sadowski, Pierre Baldi:
Deep Learning in the Natural Sciences: Applications to Physics. Braverman Readings in Machine Learning 2017: 269-297 - [c68]Forest Agostinelli, Guillaume Hocquet, Sameer Singh, Pierre Baldi:
From Reinforcement Learning to Deep Reinforcement Learning: An Overview. Braverman Readings in Machine Learning 2017: 298-328 - [i11]Peter J. Sadowski, Balint Radics, Ananya, Yasunori Yamazaki, Pierre Baldi:
Efficient Antihydrogen Detection in Antimatter Physics by Deep Learning. CoRR abs/1706.01826 (2017) - [i10]Pierre Baldi, Peter J. Sadowski, Zhiqin Lu:
Learning in the Machine: the Symmetries of the Deep Learning Channel. CoRR abs/1712.08608 (2017) - 2016
- [j113]Clovis Galiez, Christophe N. Magnan, François Coste, Pierre Baldi:
VIRALpro: a tool to identify viral capsid and tail sequences. Bioinform. 32(9): 1405-1407 (2016) - [j112]Pierre Baldi, Teresa M. Przytycka:
ISMB 2016 Proceedings. Bioinform. 32(12): 1-2 (2016) - [j111]Forest Agostinelli, Nicholas Ceglia, Babak Shahbaba, Paolo Sassone-Corsi, Pierre Baldi:
What time is it? Deep learning approaches for circadian rhythms. Bioinform. 32(12): 8-17 (2016) - [j110]Forest Agostinelli, Nicholas Ceglia, Babak Shahbaba, Paolo Sassone-Corsi, Pierre Baldi:
What time is it? Deep learning approaches for circadian rhythms. Bioinform. 32(19): 3051 (2016) - [j109]Peter J. Sadowski, David Fooshee, Niranjan Subrahmanya, Pierre Baldi:
Synergies Between Quantum Mechanics and Machine Learning in Reaction Prediction. J. Chem. Inf. Model. 56(11): 2125-2128 (2016) - [j108]Pierre Baldi, Peter J. Sadowski:
A theory of local learning, the learning channel, and the optimality of backpropagation. Neural Networks 83: 51-74 (2016) - [c67]Evan Racah, Seyoon Ko, Peter J. Sadowski, Wahid Bhimji, Craig Tull, Sang-Yun Oh, Pierre Baldi, Prabhat:
Revealing Fundamental Physics from the Daya Bay Neutrino Experiment Using Deep Neural Networks. ICMLA 2016: 892-897 - [i9]Evan Racah, Seyoon Ko, Peter J. Sadowski, Wahid Bhimji, Craig Tull, Sang-Yun Oh, Pierre Baldi, Prabhat:
Revealing Fundamental Physics from the Daya Bay Neutrino Experiment using Deep Neural Networks. CoRR abs/1601.07621 (2016) - [i8]Pierre Baldi, Kyle Cranmer, Taylor Faucett, Peter J. Sadowski, Daniel Whiteson:
Parameterized Machine Learning for High-Energy Physics. CoRR abs/1601.07913 (2016) - [i7]Pierre Baldi, Peter J. Sadowski, Zhiqin Lu:
Learning in the Machine: Random Backpropagation and the Learning Channel. CoRR abs/1612.02734 (2016) - 2015
- [j107]Vishal R. Patel, Nicholas Ceglia, Michael Zeller, Kristin Eckel-Mahan, Paolo Sassone-Corsi, Pierre Baldi:
The pervasiveness and plasticity of circadian oscillations: the coupled circadian-oscillators framework. Bioinform. 31(19): 3181-3188 (2015) - [j106]Alessandro Lusci, Michael R. Browning, David Fooshee, S. Joshua Swamidass, Pierre Baldi:
Accurate and efficient target prediction using a potency-sensitive influence-relevance voter. J. Cheminformatics 7: 63:1-63:13 (2015) - [c66]Forest Agostinelli, Matthew D. Hoffman, Peter J. Sadowski, Pierre Baldi:
Learning Activation Functions to Improve Deep Neural Networks. ICLR (Workshop) 2015 - [i6]Pierre Baldi, Peter J. Sadowski:
The Ebb and Flow of Deep Learning: a Theory of Local Learning. CoRR abs/1506.06472 (2015) - 2014
- [j105]Pierre Baldi, Peter J. Sadowski:
The dropout learning algorithm. Artif. Intell. 210: 78-122 (2014) - [j104]Ken Nagata, Arlo Z. Randall, Pierre Baldi:
Incorporating post-translational modifications and unnatural amino acids into high-throughput modeling of protein structures. Bioinform. 30(12): 1681-1689 (2014) - [j103]Christophe N. Magnan, Pierre Baldi:
SSpro/ACCpro 5: almost perfect prediction of protein secondary structure and relative solvent accessibility using profiles, machine learning and structural similarity. Bioinform. 30(18): 2592-2597 (2014) - [j102]Michael Zeller, Christophe N. Magnan, Vishal R. Patel, Paul Rigor, Leonard Sender, Pierre Baldi:
A Genomic Analysis Pipeline and Its Application to Pediatric Cancers. IEEE ACM Trans. Comput. Biol. Bioinform. 11(5): 826-839 (2014) - [c65]Davide Chicco, Peter J. Sadowski, Pierre Baldi:
Deep autoencoder neural networks for gene ontology annotation predictions. BCB 2014: 533-540 - [c64]Peter J. Sadowski, Julian Collado, Daniel Whiteson, Pierre Baldi:
Deep Learning, Dark Knowledge, and Dark Matter. HEPML@NIPS 2014: 81-87 - [c63]Peter J. Sadowski, Daniel Whiteson, Pierre Baldi:
Searching for Higgs Boson Decay Modes with Deep Learning. NIPS 2014: 2393-2401 - [c62]Julian Yarkony, Thorsten Beier, Pierre Baldi, Fred A. Hamprecht:
Parallel Multicut Segmentation via Dual Decomposition. NFMCP 2014: 56-68 - [e1]Pierre Baldi, Wei Wang:
Proceedings of the 5th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics, BCB '14, Newport Beach, California, USA, September 20-23, 2014. ACM 2014, ISBN 978-1-4503-2894-4 [contents] - [i5]Pierre Baldi, Peter J. Sadowski, Daniel Whiteson:
Enhanced Higgs to $τ^+τ^-$ Searches with Deep Learning. CoRR abs/1410.3469 (2014) - [i4]Pierre Baldi, Kenji Fukumizu, Tomaso A. Poggio:
Deep Learning: Theory, Algorithms, and Applications (NII Shonan Meeting 2014-5). NII Shonan Meet. Rep. 2014 (2014) - 2013
- [j101]Ivan Chang, Pierre Baldi:
A unifying kinetic framework for modeling oxidoreductase-catalyzed reactions. Bioinform. 29(10): 1299-1307 (2013) - [j100]Alessandro Lusci, Gianluca Pollastri, Pierre Baldi:
Deep Architectures and Deep Learning in Chemoinformatics: The Prediction of Aqueous Solubility for Drug-Like Molecules. J. Chem. Inf. Model. 53(7): 1563-1575 (2013) - [j99]David Fooshee, Alessio Andronico, Pierre Baldi:
ReactionMap: An Efficient Atom-Mapping Algorithm for Chemical Reactions. J. Chem. Inf. Model. 53(11): 2812-2819 (2013) - [j98]Peter J. Sadowski, Pierre Baldi:
Small-Molecule 3D Structure Prediction Using Open Crystallography Data. J. Chem. Inf. Model. 53(12): 3127-3130 (2013) - [c61]Pierre Baldi, Peter J. Sadowski:
Understanding Dropout. NIPS 2013: 2814-2822 - [c60]Francesco Napolitano, Roberto Tagliaferri, Pierre Baldi:
An Adaptive Reference Point Approach to Efficiently Search Large Chemical Databases. WIRN 2013: 63-74 - 2012
- [j97]Pietro di Lena, Ken Nagata, Pierre Baldi:
Deep architectures for protein contact map prediction. Bioinform. 28(19): 2449-2457 (2012) - [j96]Pierre Baldi:
Boolean autoencoders and hypercube clustering complexity. Des. Codes Cryptogr. 65(3): 383-403 (2012) - [j95]Pierre Baldi, Cristina Videira Lopes:
The Universal Campus: An open virtual 3-D world infrastructure for research and education. eLearn Mag. 2012(4): 6 (2012) - [j94]Ramzi Nasr, Rares Vernica, Chen Li, Pierre Baldi:
Speeding Up Chemical Searches Using the Inverted Index: The Convergence of Chemoinformatics and Text Search Methods. J. Chem. Inf. Model. 52(4): 891-900 (2012) - [j93]Matthew A. Kayala, Pierre Baldi:
ReactionPredictor: Prediction of Complex Chemical Reactions at the Mechanistic Level Using Machine Learning. J. Chem. Inf. Model. 52(10): 2526-2540 (2012) - [j92]Matthew A. Kayala, Pierre Baldi:
Cyber-T web server: differential analysis of high-throughput data. Nucleic Acids Res. 40(Web-Server-Issue): 553-559 (2012) - [j91]