🦜🔗 Build context-aware reasoning applications

CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image

A guidance language for controlling large language models.

links to conference publications in graph-based deep learning

A Unified Library for Parameter-Efficient and Modular Transfer Learning

PyTorch implementation of SimCLR: A Simple Framework for Contrastive Learning of Visual Representations

A PyTorch library entirely dedicated to neural differential equations, implicit models and related numerical methods

Implementation of Transformer model (originally from Attention is All You Need) applied to Time Series.

Code for our paper "Hamiltonian Neural Networks"

3DV 2021: Synergy between 3DMM and 3D Landmarks for Accurate 3D Facial Geometry

Graph Neural PDEs

Implemented Machine Learning Algorithms in Hyperbolic Geometry (MDS, K-Means, Support vector machines, etc.)

Official implementation of ICLR'24 paper, "Curiosity-driven Red Teaming for Large Language Models" (https://openreview.net/pdf?id=4KqkizXgXU)

Deep Autoencoding Gaussian Mixture Model for Unsupervised Anomaly Detection

The Energy Transformer block, in JAX

Supplementary Documents for paper Bidirectional Residual Declarative Network: A Deep Learning Framework for Robust Facial Expression Recognition

Official Implementation for DeepHGCN: Toward Deeper Hyperbolic Graph Convolutional Network