A Flexible Framework for Developing Integrated Models of Transportation Systems Using an Agent-based Approach. - Vadim Sokolov; Joshua Auld; Michael Hope (ANT/MobiWIS, 2012)

Coordinated Platoon Routing in a Metropolitan Network. - Jeffrey Larson 001; Todd S. Munson; Vadim Sokolov (CSC, 2016)

Deep Learning: A Bayesian Perspective. - Nicholas Polson; Vadim Sokolov (CoRR, 2017)

Platoon formation maximization through centralized routing and departure time coordination. - Vadim Sokolov; Jeffrey Larson 001; Todd S. Munson; Joshua Auld; Dominik Karbowski (CoRR, 2017)

Bayesian Optimization for Transportation Simulators. - Laura Schultz; Vadim Sokolov (ANT/SEIT, 2018)

Effects of Predictive Real-Time Traffic Signal Information. - Vadim Sokolov; Muhammad Imran 019; David W. Etherington; Dominik Karbowski; Aymeric Rousseau (ITSC, 2018)

Deep Reinforcement Learning for Dynamic Urban Transportation Problems. - Laura Schultz; Vadim Sokolov (CoRR, 2018)

Deep Learning. - Nicholas G. Polson; Vadim O. Sokolov (CoRR, 2018)

Deep Learning for Energy Markets. - Michael Polson; Vadim Sokolov (CoRR, 2018)

Deep Learning: Computational Aspects. - Nicholas Polson; Vadim Sokolov (CoRR, 2018)

Bayesian Particle Tracking of Traffic Flows. - Nicholas Polson; Vadim Sokolov (IEEE Trans. Intell. Transp. Syst., 2018)

FakeTables: Using GANs to Generate Functional Dependency Preserving Tables with Bounded Real Data. - Haipeng Chen 001; Sushil Jajodia; Jing Liu 024; Noseong Park; Vadim Sokolov; V. S. Subrahmanian (IJCAI, 2019)

Scalable Data Augmentation for Deep Learning. - Yuexi Wang; Nicholas G. Polson; Vadim O. Sokolov (CoRR, 2019)

Solving Large-Scale 0-1 Knapsack Problems and its Application to Point Cloud Resampling. - Duanshun Li; Jing Liu 024; Noseong Park; Dongeun Lee 001; Giridhar Ramachandran; Ali Seyedmazloom; Kookjin Lee; Chen Feng 002; Vadim Sokolov; Rajesh Ganesan (CoRR, 2019)

Clusters of Driving Behavior From Observational Smartphone Data. - Josh Warren; Jeff Lipkowitz; Vadim Sokolov (IEEE Intell. Transp. Syst. Mag., 2019)

Merging Two Cultures: Deep and Statistical Learning. - Anindya Bhadra; Jyotishka Datta; Nicholas G. Polson; Vadim Sokolov; Jianeng Xu (CoRR, 2021)

Deep Generative Models for Vehicle Speed Trajectories. - Farnaz Behnia; Dominik Karbowski; Vadim Sokolov (CoRR, 2021)

Quantum Bayes AI. - Nicholas G. Polson; Vadim Sokolov; Jianeng Xu (CoRR, 2022)

Eco-Mobility-on-Demand Fleet Control With Ride-Sharing. - Xianan Huang; Boqi Li 001; Huei Peng; Joshua A. Auld; Vadim O. Sokolov (IEEE Trans. Intell. Transp. Syst., 2022)

Deep Learning: A Tutorial. - Nick Polson; Vadim Sokolov (CoRR, 2023)

Virtual Light Sensing Technology for Fast Calculation of Daylight Autonomy Metrics. - Sergey V. Ershov; Vadim Sokolov; Vladimir A. Galaktionov; Alexey G. Voloboy (Sensors, 2023)

On the Value of Chess Squares. - Aditya Gupta; Shiva Maharaj; Nicholas Polson; Vadim Sokolov (Entropy, 2023)

Kolmogorov GAM Networks are all you need! - Sarah Polson; Vadim Sokolov (CoRR, 2025)

Generative Modeling: A Review. - Nick Polson; Vadim Sokolov (CoRR, 2025)

Generative AI for Validating Physics Laws. - Maria Nareklishvili; Nicholas Polson; Vadim Sokolov (CoRR, 2025)

Bayesian Double Descent. - Nick Polson; Vadim Sokolov (CoRR, 2025)