Neural Network Degeneration and its Relationship to the Brain. - Jacob Adamczyk (CoRR, 2020)

Utilizing Prior Solutions for Reward Shaping and Composition in Entropy-Regularized Reinforcement Learning. - Jacob Adamczyk; Argenis Arriojas; Stas Tiomkin; Rahul V. Kulkarni (AAAI, 2023)

Bounding the optimal value function in compositional reinforcement learning. - Jacob Adamczyk; Volodymyr Makarenko; Argenis Arriojas; Stas Tiomkin; Rahul V. Kulkarni (UAI, 2023)

Bayesian inference approach for entropy regularized reinforcement learning with stochastic dynamics. - Argenis Arriojas; Jacob Adamczyk; Stas Tiomkin; Rahul V. Kulkarni (UAI, 2023)

Compositionality and Bounds for Optimal Value Functions in Reinforcement Learning. - Jacob Adamczyk; Stas Tiomkin; Rahul V. Kulkarni (CoRR, 2023)

Boosting Soft Q-Learning by Bounding. - Jacob Adamczyk; Volodymyr Makarenko; Stas Tiomkin; Rahul V. Kulkarni (RLJ, 2024)

Bootstrapped Reward Shaping. - Jacob Adamczyk; Volodymyr Makarenko; Stas Tiomkin; Rahul V. Kulkarni (AAAI, 2025)

Reinforcement Learning for Control of Non-Markovian Cellular Population Dynamics. - Josiah C. Kratz; Jacob Adamczyk (ICLR, 2025)

Average-Reward Reinforcement Learning with Entropy Regularization. - Jacob Adamczyk; Volodymyr Makarenko; Stas Tiomkin; Rahul V. Kulkarni (CoRR, 2025)

Inferring Transition Dynamics from Value Functions. - Jacob Adamczyk (CoRR, 2025)

EVAL: EigenVector-based Average-reward Learning. - Jacob Adamczyk; Volodymyr Makarenko; Stas Tiomkin; Rahul V. Kulkarni (CoRR, 2025)

Exploration Behavior of Untrained Policies. - Jacob Adamczyk (CoRR, 2025)