Popular GitHub Repositories for Silver

Notes for the Reinforcement Learning course by David Silver along with implementation of various algorithms.

Data and evaluation code for the paper WikiNEuRal: Combined Neural and Knowledge-based Silver Data Creation for Multilingual NER (EMNLP 2021).

Original PyTorch implementation of the paper "Semantic Segmentation under Adverse Conditions: A Weather and Nighttime-aware Synthetic Data-based Approach", published at the British Machine Vision Conference (BMVC) 2022.

A Jax/Stax implementation of the general meta learning paper: Oh, J., Hessel, M., Czarnecki, W.M., Xu, Z., van Hasselt, H.P., Singh, S. and Silver, D., 2020. Discovering reinforcement learning algorithms. Advances in Neural Information Processing Systems, 33.

A jax/stax implementation of: Mnih, V., Kavukcuoglu, K., Silver, D., Rusu, A.A., Veness, J., Bellemare, M.G., Graves, A., Riedmiller, M., Fidjeland, A.K., Ostrovski, G. and Petersen, S., 2015. Human-level control through deep reinforcement learning. nature, 518(7540), pp.529-533.

Original PyTorch implementation of the paper "Leveraging Synthetic Data to Learn Video Stabilization Under Adverse Conditions", published at the EEE/CVF Winter Conference on Applications of Computer Vision (WACV) 2024.

Grunt is a Python chatbot that was inspired by orcs from the Warcraft games. Orcs aren’t exactly known for their silver tongue and Grunt is no different. This is a very basic chatbot that can only give simple replies to very specific questions but the goal of this project is to make Grunt more and more sophisticated as time progressess.

End‑to‑end pipelines, notebooks and configs for assembling the multilingual OmniGEC silver‑standard corpus (WikiEdits, Reddit, UberText, MultiGEC‑25) and preparing it for model training

Implementing assignment easy-21 of RL course by David Silver

IMage to MUsic sequence for social network service applications! DCS silver prize!

1. Fine-tune DistilBERT on NLI and dentify the some salient or toxic features that the model learnt. 2. Sample annotations techniques and production of silver label using (EDA and Back Translation).

A curated collection of papers combining Self-Supervised Learning (SSL) with Reinforcement Learning (RL) in the context of Large Language Models (LLMs), toward autonomous agents in the Era of Experience. Inspired by “Welcome to the Era of Experience” (Silver & Sutton, 2025).