An implementation of the efficient attention module.
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Updated
Nov 30, 2020 - Python
An implementation of the efficient attention module.
TalkToModel gives anyone with the powers of XAI through natural language conversations 💬!
Code for the paper "Thermodynamics-informed graph neural networks" published in IEEE Transactions on Artificial Intelligence (TAI).
Single-file pytorch implementation of hybrid-SAC
An open source implementation of the paper: "Sequential Diagnosis with Language Models" From Microsoft Built with Swarms Framework
PyTorch version for the "Dual-Dtream Shallow Networks for Facial Micro-Expression Recognition"
A minimal PyTorch implementation of Flow Matching for Generative Modeling.
[ACM MM22] Mimicking the Annotation Process for Recognizing the Micro Expressions
Original Pytorch Implementation of FLAME: Facial Landmark Heatmap Activated Multimodal Gaze Estimation
PyTorch implementation of DINO (Self-Distillation with No Labels) from scratch.
Coding-agent harness for continuous contribution — discovers, implements & validates your next high-fit change as a review-ready draft PR you decide on.
Code for the paper "Structure-preserving neural networks" published in Journal of Computational Physics (JCP).
Python implementation of Efficient Graph-Based Image Segmentation.
Code for the paper "Deep learning of thermodynamics-aware reduced-order models from data" published in Computer Methods in Applied Mechanics and Engineering (CMAME).
Unsupervised specificity-guided optimization of Image Captioning models to encourage meaningful diversity in the generated captions. Code for the paper Generating Diverse and Meaningful Captions: Unsupervised Specificity Optimization for Image Captioning (Lindh et al., 2018).
Scale-recurrent Network for Deep Image Deblurring with neural networks
Unofficial open-source PyTorch implementation of the OLMo Hybrid architecture introduced by the Allen Institute for AI (Ai2).
Open reproduction of NVIDIA's AVO paper (arXiv:2603.24517): evolutionary search where an autonomous coding agent IS the variation operator — Vary(P)=Agent(P,K,f). Runs on the Claude Code or Codex session you already have.
A minimal implementation of Score-Based Generative Modeling through SDEs
re-implementaion of "A watermark for Large Language Models" ( https://arxiv.org/abs/2301.10226 )
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