Alexander Shmakov

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 26

Top Topics

Particle Physics

Reinforcement Learning

Diffusion Models

Top Venues

IEEE ACM Trans. Comput. Biol. Bioinform.

Publications

Nathan Huetsch, Javier Mariño Villadamigo, Alexander Shmakov, Sascha Diefenbacher, Vinicius Mikuni, Theo Heimel, Michael James Fenton, Kevin Greif, Benjamin Nachman, Daniel Whiteson, Anja Butter, Tilman Plehn
The Landscape of Unfolding with Machine Learning. CoRR (2024)
Alexander Shmakov, Kevin Greif, Michael James Fenton, Aishik Ghosh, Pierre Baldi, Daniel Whiteson
Full Event Particle-Level Unfolding with Variable-Length Latent Variational Diffusion. CoRR (2024)
Soumyendu Sarkar, Vineet Gundecha, Sahand Ghorbanpour, Alexander Shmakov, Ashwin Ramesh Babu, Avisek Naug, Alexandre Pichard, Mathieu Cocho
Function Approximation for Reinforcement Learning Controller for Energy from Spread Waves. CoRR (2024)
Mohammadamin Tavakoli, Pierre Baldi, Ann Marie Carlton, Yin Ting T. Chiu, Alexander Shmakov, David Van Vranken
AI for Interpretable Chemistry: Predicting Radical Mechanistic Pathways via Contrastive Learning. NeurIPS (2023)
Alexander Shmakov, Avisek Naug, Vineet Gundecha, Sahand Ghorbanpour, Ricardo Luna Gutierrez, Ashwin Ramesh Babu, Antonio Guillen, Soumyendu Sarkar
RTDK-BO: High Dimensional Bayesian Optimization with Reinforced Transformer Deep kernels. CoRR (2023)
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 (2023)
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. NeurIPS (2023)
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 (2023)
Soumyendu Sarkar, Ashwin Ramesh Babu, Sajad Mousavi, Vineet Gundecha, Sahand Ghorbanpour, Alexander Shmakov, Ricardo Luna Gutierrez, Antonio Guillen, Avisek Naug
Robustness with Black-Box Adversarial Attack using Reinforcement Learning. SafeAI@AAAI (2023)
Soumyendu Sarkar, Vineet Gundecha, Sahand Ghorbanpour, Alexander Shmakov, Ashwin Ramesh Babu, Avisek Naug, Alexandre Pichard, Mathieu Cocho
Function Approximation for Reinforcement Learning Controller for Energy from Spread Waves. IJCAI (2023)
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 (2023)
Alexander Shmakov, Alejandro Yankelevich, Jianming Bian, Pierre Baldi
Interpretable Joint Event-Particle Reconstruction for Neutrino Physics at NOvA with Sparse CNNs and Transformers. CoRR (2023)
Alexander Shmakov, Avisek Naug, Vineet Gundecha, Sahand Ghorbanpour, Ricardo Luna Gutierrez, Ashwin Ramesh Babu, Antonio Guillen, Soumyendu Sarkar
RTDK-BO: High Dimensional Bayesian Optimization with Reinforced Transformer Deep kernels. CASE (2023)
Soumyendu Sarkar, Vineet Gundecha, Alexander Shmakov, Sahand Ghorbanpour, Ashwin Ramesh Babu, Paolo Faraboschi, Mathieu Cocho, Alexandre Pichard, Jonathan Fievez
Multi-Agent Reinforcement Learning Controller to Maximize Energy Efficiency for Multi-Generator Industrial Wave Energy Converter. AAAI (2022)
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 (2022)
Mohammadamin Tavakoli, Alexander Shmakov, Francesco Ceccarelli, Pierre Baldi
Rxn Hypergraph: a Hypergraph Attention Model for Chemical Reaction Representation. CoRR (2022)
Soumyendu Sarkar, Vineet Gundecha, Sahand Ghorbanpour, Alexander Shmakov, Ashwin Ramesh Babu, Alexandre Pichard, Mathieu Cocho
Skip Training for Multi-Agent Reinforcement Learning Controller for Industrial Wave Energy Converters. CASE (2022)
Soumyendu Sarkar, Vineet Gundecha, Sahand Ghorbanpour, Alexander Shmakov, Ashwin Ramesh Babu, Alexandre Pichard, Mathieu Cocho
Skip Training for Multi-Agent Reinforcement Learning Controller for Industrial Wave Energy Converters. CoRR (2022)
Forest Agostinelli, Alexander Shmakov, Stephen McAleer, Roy Fox, Pierre Baldi
A* Search Without Expansions: Learning Heuristic Functions with Deep Q-Networks. CoRR (2021)
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 (2021)
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 (2020)
Stephen McAleer, Forest Agostinelli, Alexander Shmakov, Pierre Baldi
Solving the Rubik's Cube with Approximate Policy Iteration. ICLR (Poster) (2019)
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) (2019)
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 (2019)
Forest Agostinelli, Stephen McAleer, Alexander Shmakov, Pierre Baldi
Solving the Rubik's cube with deep reinforcement learning and search. Nat. Mach. Intell. 1 (8) (2019)
Stephen McAleer, Forest Agostinelli, Alexander Shmakov, Pierre Baldi
Solving the Rubik's Cube Without Human Knowledge. CoRR (2018)