Vadim Sokolov

According to our database, Vadim Sokolov authored at least 34 papers between 2012 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

Photons = Tokens: The Physics of AI and the Economics of Knowledge.

Alec Litowitz, Nick Polson, Vadim Sokolov

CoRR, March, 2026

Generative Bayesian Computation as a Scalable Alternative to Gaussian Process Surrogates.

Nick Polson, Vadim Sokolov

CoRR, February, 2026

Fast Compute for ML Optimization.

Nick Polson, Vadim Sokolov

CoRR, February, 2026

Bayesian Methods for the Navier-Stokes Equations.

Nicholas Polson, Vadim Sokolov

CoRR, February, 2026

Horseshoe Mixtures-of-Experts (HS-MoE).

Nick Polson, Vadim Sokolov

CoRR, January, 2026

PyGREET: A modular Python platform of the GREET life cycle analysis model for technology assessment.

Jose D. Hernandez-Betancur, Tom Sykora, Longwen Ou, Thomas Hamori, Vadim Sokolov, Amgad Elgowainy, Hao Cai, Michael Wang

Environ. Model. Softw., 2026

2025

Bayesian Double Descent.

Nick Polson, Vadim Sokolov

CoRR, July, 2025

Generative AI for Validating Physics Laws.

Maria Nareklishvili, Nicholas Polson, Vadim Sokolov

CoRR, March, 2025

Generative Modeling: A Review.

Nick Polson, Vadim Sokolov

CoRR, January, 2025

Generative AI for Bayesian Computation.

Nick Polson, Vadim Sokolov

Entropy, 2025

Kolmogorov GAM Networks Are All You Need!

Sarah Polson, Vadim Sokolov

Entropy, 2025

2024

Generative Bayesian Computation for Maximum Expected Utility.

Nick Polson, Fabrizio Ruggeri, Vadim Sokolov

Entropy, 2024

2023

On the Value of Chess Squares.

Aditya Gupta, Shiva Maharaj, Nicholas Polson, Vadim Sokolov

Entropy, October, 2023

Virtual Light Sensing Technology for Fast Calculation of Daylight Autonomy Metrics.

Sergey V. Ershov, Vadim Sokolov, Vladimir A. Galaktionov, Alexey G. Voloboy

Sensors, February, 2023

Deep Learning: A Tutorial.

Nick Polson, Vadim Sokolov

CoRR, 2023

2022

Eco-Mobility-on-Demand Fleet Control With Ride-Sharing.

Xianan Huang, Boqi Li, Huei Peng, Joshua A. Auld, Vadim O. Sokolov

IEEE Trans. Intell. Transp. Syst., 2022

Quantum Bayes AI.

Nicholas G. Polson, Vadim Sokolov, Jianeng Xu

CoRR, 2022

2021

Deep Generative Models for Vehicle Speed Trajectories.

Farnaz Behnia, Dominik Karbowski, Vadim Sokolov

CoRR, 2021

Merging Two Cultures: Deep and Statistical Learning.

Anindya Bhadra, Jyotishka Datta, Nicholas G. Polson, Vadim Sokolov, Jianeng Xu

CoRR, 2021

2019

Clusters of Driving Behavior From Observational Smartphone Data.

Josh Warren, Jeff Lipkowitz, Vadim Sokolov

IEEE Intell. Transp. Syst. Mag., 2019

Solving Large-Scale 0-1 Knapsack Problems and its Application to Point Cloud Resampling.

Duanshun Li, Jing Liu, Noseong Park, Dongeun Lee, Giridhar Ramachandran, Ali Seyedmazloom, Kookjin Lee, Chen Feng, Vadim Sokolov, Rajesh Ganesan

CoRR, 2019

Scalable Data Augmentation for Deep Learning.

Yuexi Wang, Nicholas G. Polson, Vadim O. Sokolov

CoRR, 2019

FakeTables: Using GANs to Generate Functional Dependency Preserving Tables with Bounded Real Data.

Haipeng Chen, Sushil Jajodia, Jing Liu, Noseong Park, Vadim Sokolov, V. S. Subrahmanian

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

2018

Bayesian Particle Tracking of Traffic Flows.

Nicholas Polson, Vadim Sokolov

IEEE Trans. Intell. Transp. Syst., 2018

Deep Learning: Computational Aspects.

Nicholas Polson, Vadim Sokolov

CoRR, 2018

Deep Learning for Energy Markets.

Michael Polson, Vadim Sokolov

CoRR, 2018

Deep Learning.

Nicholas G. Polson, Vadim O. Sokolov

CoRR, 2018

Deep Reinforcement Learning for Dynamic Urban Transportation Problems.

Laura Schultz, Vadim Sokolov

CoRR, 2018

Effects of Predictive Real-Time Traffic Signal Information.

Vadim Sokolov, Muhammad Imran, David W. Etherington, Dominik Karbowski, Aymeric Rousseau

Proceedings of the 21st International Conference on Intelligent Transportation Systems, 2018

Bayesian Optimization for Transportation Simulators.

Laura Schultz, Vadim Sokolov

Proceedings of the 9th International Conference on Ambient Systems, 2018

2017

Platoon formation maximization through centralized routing and departure time coordination.

Vadim Sokolov, Jeffrey Larson, Todd S. Munson, Joshua Auld, Dominik Karbowski

CoRR, 2017

Deep Learning: A Bayesian Perspective.

Nicholas Polson, Vadim Sokolov

CoRR, 2017

2016

Coordinated Platoon Routing in a Metropolitan Network.

Jeffrey Larson, Todd S. Munson, Vadim Sokolov

Proceedings of the 2016 Proceedings of the Seventh SIAM Workshop on Combinatorial Scientific Computing, 2016

2012

A Flexible Framework for Developing Integrated Models of Transportation Systems Using an Agent-based Approach.

Vadim Sokolov, Joshua Auld, Michael Hope

Proceedings of the 3rd International Conference on Ambient Systems, 2012