SSubhnil
PhD candidate at Trinity College Dublin, Ireland. I work on RL, causality, latent variables and multi-agent systems.
Trinity College DublinDublin, Ireland
Pinned Repositories
BAC-DAC-gym
Bayesian Actor-Critic with Neural Networks. Developing an OpenAI Gym toolkit for Bayesian AC reinforcement learning.
Causal-Gridworld
Testing the causal implications of the wind in the gridworld environment. The wind is the confounder.
CausalBench
Official data and code for our paper Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning
CoGen_Benchmarking
Benchmarking existing RL algorithms including model-free and model-based approaches on confounded versions of popular environments. Tests generalization and sample efficiency.
dreamerv3-benchmod
Modifying DreamerV3 for benchmarking in confounded environments
Lane-Lines-Detection-Python-OpenCV
Lane Lines Detection using Python and OpenCV for self-driving car
mamba-test
Edited version of original mamba https://github.com/zoharri/mamba
RacingCARLA
Learning Model Predictive Control (LMPC) for autonomous racing in CARLA 3D environment.
RacingLMPC
Vehicle-Dynamics-Toolkit
Some advanced tools for race car design - Steady state and transient dynamics, Tyre Data synthesis
SSubhnil's Repositories
SSubhnil/RacingCARLA
Learning Model Predictive Control (LMPC) for autonomous racing in CARLA 3D environment.
SSubhnil/BAC-DAC-gym
Bayesian Actor-Critic with Neural Networks. Developing an OpenAI Gym toolkit for Bayesian AC reinforcement learning.
SSubhnil/RacingLMPC
SSubhnil/Vehicle-Dynamics-Toolkit
Some advanced tools for race car design - Steady state and transient dynamics, Tyre Data synthesis
SSubhnil/Causal-Gridworld
Testing the causal implications of the wind in the gridworld environment. The wind is the confounder.
SSubhnil/CausalBench
Official data and code for our paper Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning
SSubhnil/CoGen_Benchmarking
Benchmarking existing RL algorithms including model-free and model-based approaches on confounded versions of popular environments. Tests generalization and sample efficiency.
SSubhnil/dreamerv3-benchmod
Modifying DreamerV3 for benchmarking in confounded environments
SSubhnil/Lane-Lines-Detection-Python-OpenCV
Lane Lines Detection using Python and OpenCV for self-driving car
SSubhnil/mamba-test
Edited version of original mamba https://github.com/zoharri/mamba