Python library for solving reinforcement learning (RL) problems using generative models.
-
Updated
May 28, 2024 - Python
Python library for solving reinforcement learning (RL) problems using generative models.
MIDI / symbolic music tokenizers for Deep Learning models 🎶
An implementation of the GPT(generative pretrained transformer) model, from scratch, which produces Shakespearean text by training on the dialogues written by Shakespeare along with the GPT Encoder.
Face Generation using Guided Diffusion Models, part of a masters thesis project
A library to model multivariate data using copulas.
Design of target-focused libraries by probing continuous fingerprint space with recurrent neural networks. The repository accompanies a research paper which is currently under review (08.04.24)
Synthetic data generation for tabular data
Space Group Informed Transformer for Crystalline Materials Generation
This is an open collection of state-of-the-art (SOTA), novel Text to X (X can be everything) methods (papers, codes and datasets).
[NeurIPS 2023] T2T: From Distribution Learning in Training to Gradient Search in Testing for Combinatorial Optimization
Repo for all the SRIP 2024 work at CVIG Lab IITGN under Prof. Shanmuganathan Raman
A Comprehensive Survey of Forgetting in Deep Learning Beyond Continual Learning. arXiv:2307.09218.
Team LLMAO's submission for EY Techathon 4.0 addresses the education challenge with AI-powered content generation, automated grading, and personalized learning. Our prototype enhances accessibility, user engagement, and learning progress metrics, aiming to revolutionize education for students like Rani facing language and infrastructure barriers.
🧬 Generative modeling of regulatory DNA sequences with diffusion probabilistic models 💨
CraftsMan: High-fidelity Mesh Generation with 3D Native Diffusion and Interactive Geometry Refiner
Official Implementation (Pytorch) of "DDMI: Domain-Agnostic Latent Diffusion Models for Synthesizing High-Quality Implicit Neural Representations", ICLR 2024
scAR (single-cell Ambient Remover) is a deep learning model for removal of the ambient signals in droplet-based single cell omics
📰 Must-read papers on Diffusion Models for Text Generation 🔥
[Arxiv 2024] From Parts to Whole: A Unified Reference Framework for Controllable Human Image Generation
[ICLR24 (Spotlight)] "SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and Generation" by Chongyu Fan*, Jiancheng Liu*, Yihua Zhang, Eric Wong, Dennis Wei, Sijia Liu
Add a description, image, and links to the generative-model topic page so that developers can more easily learn about it.
To associate your repository with the generative-model topic, visit your repo's landing page and select "manage topics."