Chronos: Pretrained (Language) Models for Probabilistic Time Series Forecasting

Codebase for Attentive Neural Hawkes Process (A-NHP) and Attentive Neural Datalog Through Time (A-NDTT)

[ICLR 2023] MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP Initialization

Language Modeling with the H3 State Space Model

A repo for distributed training of language models with Reinforcement Learning via Human Feedback (RLHF)

Code for the paper Fine-Tuning Language Models from Human Preferences

Sequence Modeling with Structured State Spaces

Implementation of 1D, 2D, and 3D FFT convolutions in PyTorch. Much faster than direct convolutions for large kernel sizes.

Codes for "CSDI: Conditional Score-based Diffusion Models for Probabilistic Time Series Imputation"

Deep generative modeling for time-stamped heterogeneous data, enabling high-fidelity models for a large variety of spatio-temporal domains.

Implementations of basic RL algorithms with minimal lines of codes! (pytorch based)

Code for Transformer Hawkes Process, ICML 2020.

Code for "GP-ConvCNP: Better Generalization for Convolutional Conditional Neural Processes on Time Series Data"

The Electricity Transformer dataset is collected to support the further investigation on the long sequence forecasting problem.

Code reproducing Neural Collapse phenomenon on MSE and cross-entropy loss

Code for Benchmarks, Algorithms, and Metrics for Hierarchical Disentanglement

Notebooks about Bayesian methods for machine learning

Pytorch implementation of Neural Processes for functions and images 🎆

Pytorch implementation of neural processes and variants

Code for the Neural Processes website and replication of 4 papers on NPs. Pytorch implementation.

A Comprehensive Roadmap to Mathematics

Practical Python Programming (course by @dabeaz)