Alexander Shmakov

According to our database, Alexander Shmakov authored at least 21 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

The Landscape of Unfolding with Machine Learning.

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

CoRR, 2024

Full Event Particle-Level Unfolding with Variable-Length Latent Variational Diffusion.

Alexander Shmakov, Kevin Greif, Michael James Fenton, Aishik Ghosh, Pierre Baldi, Daniel Whiteson

CoRR, 2024

2023

Extended Symmetry Preserving Attention Networks for LHC Analysis.

Michael James Fenton, Alexander Shmakov, Hideki Okawa, Yuji Li, Ko-Yang Hsiao, Shih-Chieh Hsu, Daniel Whiteson, Pierre Baldi

CoRR, 2023

Interpretable Joint Event-Particle Reconstruction for Neutrino Physics at NOvA with Sparse CNNs and Transformers.

Alexander Shmakov, Alejandro Yankelevich, Jianming Bian, Pierre Baldi

CoRR, 2023

AI for Interpretable Chemistry: Predicting Radical Mechanistic Pathways via Contrastive Learning.

Mohammadamin Tavakoli, Pierre Baldi, Ann Marie Carlton, Yin Ting T. Chiu, Alexander Shmakov, David Van Vranken

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

End-To-End Latent Variational Diffusion Models for Inverse Problems in High Energy Physics.

Alexander Shmakov, Kevin Greif, Michael James Fenton, Aishik Ghosh, Pierre Baldi, Daniel Whiteson

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Function Approximation for Reinforcement Learning Controller for Energy from Spread Waves.

Soumyendu Sarkar, Vineet Gundecha, Sahand Ghorbanpour, Alexander Shmakov, Ashwin Ramesh Babu, Avisek Naug, Alexandre Pichard, Mathieu Cocho

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

RTDK-BO: High Dimensional Bayesian Optimization with Reinforced Transformer Deep kernels.

Alexander Shmakov, Avisek Naug, Vineet Gundecha, Sahand Ghorbanpour, Ricardo Luna Gutierrez, Ashwin Ramesh Babu, Antonio Guillen, Soumyendu Sarkar

Proceedings of the 19th IEEE International Conference on Automation Science and Engineering, 2023

Robustness with Black-Box Adversarial Attack using Reinforcement Learning.

Soumyendu Sarkar, Ashwin Ramesh Babu, Sajad Mousavi, Vineet Gundecha, Sahand Ghorbanpour, Alexander Shmakov, Ricardo Luna Gutierrez, Antonio Guillen, Avisek Naug

Proceedings of the Workshop on Artificial Intelligence Safety 2023 (SafeAI 2023) co-located with the Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI 2023), 2023

2022

Deep Learning Models of the Discrete Component of the Galactic Interstellar Gamma-Ray Emission.

Alexander Shmakov, Mohammadamin Tavakoli, Pierre Baldi, Christopher M. Karwin, Alex Broughton, Simona Murgia

CoRR, 2022

Rxn Hypergraph: a Hypergraph Attention Model for Chemical Reaction Representation.

Mohammadamin Tavakoli, Alexander Shmakov, Francesco Ceccarelli, Pierre Baldi

CoRR, 2022

Skip Training for Multi-Agent Reinforcement Learning Controller for Industrial Wave Energy Converters.

Soumyendu Sarkar, Vineet Gundecha, Sahand Ghorbanpour, Alexander Shmakov, Ashwin Ramesh Babu, Alexandre Pichard, Mathieu Cocho

Proceedings of the 18th IEEE International Conference on Automation Science and Engineering, 2022

Multi-Agent Reinforcement Learning Controller to Maximize Energy Efficiency for Multi-Generator Industrial Wave Energy Converter.

Soumyendu Sarkar, Vineet Gundecha, Alexander Shmakov, Sahand Ghorbanpour, Ashwin Ramesh Babu, Paolo Faraboschi, Mathieu Cocho, Alexandre Pichard, Jonathan Fievez

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

SPANet: Generalized Permutationless Set Assignment for Particle Physics using Symmetry Preserving Attention.

Alexander Shmakov, Michael James Fenton, Ta-Wei Ho, Shih-Chieh Hsu, Daniel Whiteson, Pierre Baldi

CoRR, 2021

A* Search Without Expansions: Learning Heuristic Functions with Deep Q-Networks.

Forest Agostinelli, Alexander Shmakov, Stephen McAleer, Roy Fox, Pierre Baldi

CoRR, 2021

2020

Permutationless Many-Jet Event Reconstruction with Symmetry Preserving Attention Networks.

Michael James Fenton, Alexander Shmakov, Ta-Wei Ho, Shih-Chieh Hsu, Daniel Whiteson, Pierre Baldi

CoRR, 2020

2019

Deep Learning for Drug Discovery and Cancer Research: Automated Analysis of Vascularization Images.

Gregor Urban, Kevin Bache, Duc T. T. Phan, Agua Sobrino, Alexander Shmakov, Stephanie J. Hachey, Christopher C. W. Hughes, Pierre Baldi

IEEE ACM Trans. Comput. Biol. Bioinform., 2019

Solving the Rubik's cube with deep reinforcement learning and search.

Forest Agostinelli, Stephen McAleer, Alexander Shmakov, Pierre Baldi

Nat. Mach. Intell., 2019

ColosseumRL: A Framework for Multiagent Reinforcement Learning in N-Player Games.

Alexander Shmakov, John B. Lanier, Stephen McAleer, Rohan Achar, Cristina V. Lopes, Pierre Baldi

CoRR, 2019

Solving the Rubik's Cube with Approximate Policy Iteration.

Stephen McAleer, Forest Agostinelli, Alexander Shmakov, Pierre Baldi

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Solving the Rubik's Cube Without Human Knowledge.

Stephen McAleer, Forest Agostinelli, Alexander Shmakov, Pierre Baldi

CoRR, 2018