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A curated list of awesome Claude Skills, resources, and tools for customizing Claude AI workflows
Official implementation of "DDN: Dual-domain Dynamic Normalization for Non-stationary Time Series Forecasting" (NeurIPS 2024)
Uncertainty Quantification in Hydrology: CAMELS data. Streamflow and River Basin Attribute Estimation
PDF Parser for AI-ready data. Automate PDF accessibility. Open-source.
AI agents running research on single-GPU nanochat training automatically
Time Series Management and Analysis for Hydrological Modelling
Python library to train neural networks with a strong focus on hydrological applications.
Real-time global intelligence dashboard. AI-powered news aggregation, geopolitical monitoring, and infrastructure tracking in a unified situational awareness interface
RevIN: Reversible Instance Normalization For Accurate Time-series Forecasting Against Distribution Shift
Physics Informed Deep Learning: Data-driven Solutions and Discovery of Nonlinear Partial Differential Equations
Assist in organizing your piles of documents, resulting from scanners, e-mails and other sources with miminal effort.
A map with millions of events from Wikipedia
PyHessian is a Pytorch library for second-order based analysis and training of Neural Networks
DuckDB is an analytical in-process SQL database management system
Codebase for paper ToolVQA: A Dataset for Multi-step Reasoning VQA with External Tools
Code for visualizing the loss landscape of neural nets
Repository for "FreDF: Learning to Forecast in the Transformed Domain"
A unified framework for machine learning with time series
Official implementation of "TimeBridge: Non-Stationarity Matters for Long-term Time Series Forecasting" (ICML 2025)
MultiDoc2Dial: Modeling Dialogues Grounded in Multiple Documents
A Synthetic Data Tuned Retriever Framework for Documents Understanding
A hybrid approach for hydrological modelling that combines process based approach with Deep Neural Networks
Quantile regression ensemble of DeepGR4J hydrological model
A library for efficient similarity search and clustering of dense vectors.
A high-throughput and memory-efficient inference and serving engine for LLMs