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Official repo for "LongRAG: Enhancing Retrieval-Augmented Generation with Long-context LLMs".
A library to generate synthetic time series data by easy-to-use factors and generator
MOMENT: A Family of Open Time-series Foundation Models
An extremely fast Python package installer and resolver, written in Rust.
Chronos: Pretrained (Language) Models for Probabilistic Time Series Forecasting
Devika is an Agentic AI Software Engineer that can understand high-level human instructions, break them down into steps, research relevant information, and write code to achieve the given objective…
[ICML2024] Unified Training of Universal Time Series Forecasting Transformers
Pytorch implementation of RED-SDS (NeurIPS 2021).
Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting
A new markup-based typesetting system that is powerful and easy to learn.
Friends don't let friends make certain types of data visualization - What are they and why are they bad.
PyTorch implementation of the NCDSSM models presented in the ICML '23 paper "Neural Continuous-Discrete State Space Models for Irregularly-Sampled Time Series".
Official PyTorch implementation of TSDiff models presented in the NeurIPS 2023 paper "Predict, Refine, Synthesize: Self-Guiding Diffusion Models for Probabilistic Time Series Forecasting"
Reasoning in Large Language Models: Papers and Resources, including Chain-of-Thought, Instruction-Tuning and Multimodality.
Fast & Simple repository for pre-training and fine-tuning T5-style models
Dromedary: towards helpful, ethical and reliable LLMs.
Probabilistic time series modeling in Python
This is a collection of code samples aimed at illustrating temporal parallelization methods for sequential data.
lxxue / prefix_sum
Forked from mattdean1/cudaA PyTorch wrapper of parallel exclusive scan in CUDA
A PyTorch library entirely dedicated to neural differential equations, implicit models and related numerical methods
list of papers, code, and other resources
A professionally curated list of awesome resources (paper, code, data, etc.) on transformers in time series.
A playbook for systematically maximizing the performance of deep learning models.
pandas on AWS - Easy integration with Athena, Glue, Redshift, Timestream, Neptune, OpenSearch, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (…