"Graph Neural Controlled Differential Equations for Traffic Forecasting", AAAI 2022

[NeurIPS NCW 2024] Official implementation for the paper "Neural Compression for Multispectral Satellite Images"

[NeurIPS'24] Generalizing Weather Forecast to Fine-grained Temporal Scales via Physics-AI Hybrid Modeling

Contains the implementation of the paper "Implicit Neural Representation for Image Compression" at ECCV 2022

Code release for NeRF (Neural Radiance Fields)

KAN (Kolmogorov-Arnold Network)-based Recommendation (CF)

Inducing Point Operator Transformer: A Flexible and Scalable Architecture for Solving PDEs (AAAI 2024)

Blurring-Sharpening Process Models for Collaborative Filtering, SIGIR'23

[ACL 2024 Findings & ICLR 2024 WS] An Evaluator VLM that is open-source, offers reproducible evaluation, and inexpensive to use. Specifically designed for fine-grained evaluation on customized scor…

[ICLR 2024 & NeurIPS 2023 WS] An Evaluator LM that is open-source, offers reproducible evaluation, and inexpensive to use. Specifically designed for fine-grained evaluation on a customized score ru…

Source code for Separable PINN

Refine high-quality datasets and visual AI models

OpenReivew Submission Visualization (ICLR 2024/2025)

Myriad is a real-world testbed that aims to bridge trajectory optimization and deep learning.

A curated list of resources on implicit neural representations.

LORD: Lower-Dimensional Embedding of Log-Signature in Neural Rough Differential Equations(ICLR 2022)

Physics Informed Deep Learning: Data-driven Solutions and Discovery of Nonlinear Partial Differential Equations

[AAAI-23 Oral] Official implementation of the paper "Are Transformers Effective for Time Series Forecasting?"

Simple PyTorch Implementation of Physics Informed Neural Network (PINN)

Neural Laplace: Differentiable Laplace Reconstructions for modelling any time observation with O(1) complexity.

Multiwavelets-based operator model

Learning in infinite dimension with neural operators.