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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) - [i50]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) - [i49]Geunwoo Kim, Pierre Baldi, Stephen McAleer:
Language Models can Solve Computer Tasks. CoRR abs/2303.17491 (2023) - [i48]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) - [i47]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) - [i46]Sungduk Yu, Walter M. Hannah, Liran Peng, Mohamed Aziz Bhouri, Ritwik Gupta, Jerry Lin, Björn Lütjens, Justus C. Will, Tom Beucler, Bryce E. Harrop, Benjamin R. Hillman, Andrea M. Jenney, Savannah L. Ferretti, Nana Liu, Anima Anandkumar, Noah D. Brenowitz, Veronika Eyring, Pierre Gentine, Stephan Mandt, Jaideep Pathak, Carl Vondrick, Rose Yu, Laure Zanna, Ryan P. Abernathey, Fiaz Ahmed, David C. Bader, Pierre Baldi, Elizabeth A. Barnes, Gunnar Behrens, Christopher S. Bretherton, Julius J. M. Busecke, Peter M. Caldwell, Wayne Chuang, Yilun Han, Yu Huang, Fernando Iglesias-Suarez, Sanket R. Jantre, Karthik Kashinath, Marat Khairoutdinov, Thorsten Kurth, Nicholas J. Lutsko, Po-Lun Ma, Griffin Mooers, J. David Neelin, David A. Randall, Sara Shamekh, Akshay Subramaniam, Mark A. Taylor, et al.:
ClimSim: An open large-scale dataset for training high-resolution physics emulators in hybrid multi-scale climate simulators. CoRR abs/2306.08754 (2023) - [i45]Kolby Nottingham, Yasaman Razeghi, Kyungmin Kim, JB Lanier, Pierre Baldi, Roy Fox, Sameer Singh:
Selective Perception: Optimizing State Descriptions with Reinforcement Learning for Language Model Actors. CoRR abs/2307.11922 (2023) - [i44]Michael James Fenton, Alexander Shmakov, Hideki Okawa, Yuji Li, Ko-Yang Hsiao, Shih-Chieh Hsu, Daniel Whiteson, Pierre Baldi:
Extended Symmetry Preserving Attention Networks for LHC Analysis. CoRR abs/2309.01886 (2023) - [i43]Mohammadamin Tavakoli, Yin Ting T. Chiu, Alexander Shmakov, Ann Marie Carlton, David Van Vranken, Pierre Baldi:
AI for Interpretable Chemistry: Predicting Radical Mechanistic Pathways via Contrastive Learning. CoRR abs/2311.01118 (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]