Signature Kernel Computation Using Power Series

[NeurIPS'25] Sequence Modeling with Spectral Mean Flows, in PyTorch

⚡ TabPFN: Foundation Model for Tabular Data ⚡

A high-performance library for path signatures and rough path methods on CPU and GPU

Compare the existing methods on signature based learning of stochastic processes

Differentiable computations for the signature-PDE-kernel on CPU and GPU.

A Lean companion to Analysis I

Official Implementation of Variational Inference for SDEs Driven by Fractional Noise

Multiresolution Adaptive Numerical Environment for Scientific Simulation

[Neurips 2024] A benchmark suite for autoregressive neural emulation of PDEs. (≥46 PDEs in 1D, 2D, 3D; Differentiable Physics; Unrolled Training; Rollout Metrics)

Official reference implementation of NeurIPS 2024 paper "Energy-based Epistemic Uncertainty for Graph Neural Networks"

This repository contains the resources on graph neural network (GNN) considering heterophily.

[ICML 2022] pGNN, p-Laplacian Based Graph Neural Networks

Official implementation for "AutoTimes: Autoregressive Time Series Forecasters via Large Language Models"

[ICLR 2024] Official implementation of " 🦙 Time-LLM: Time Series Forecasting by Reprogramming Large Language Models"

Several Coding Patterns for Solving Data Structures and Algorithms Problems during Interviews

Repo to accompany my mastering LLM engineering course

XRO: Extended nonlinear Recharge Oscillator model

Train transformer language models with reinforcement learning.

A modular RL library to fine-tune language models to human preferences

Discovering Data-driven Hypotheses in the Wild

Python codes for Introduction to Computational Stochastic PDE

An Open-Ended Embodied Agent with Large Language Models

Official implementation of the paper "FourierGNN: Rethinking Multivariate Time Series Forecasting from a Pure Graph Perspective"