OpenAssistant is a chat-based assistant that understands tasks, can interact with third-party systems, and retrieve information dynamically to do so.
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ncnn is a high-performance neural network inference framework optimized for the mobile platform
Speech-to-text, text-to-speech, speaker diarization, speech enhancement, source separation, and VAD using next-gen Kaldi with onnxruntime without Internet connection. Support embedded systems, Android, iOS, HarmonyOS, Raspberry Pi, RISC-V, RK NPU, Axera NPU, Ascend NPU, x86_64 servers, websocket server/client, support 12 programming languages
The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery 🧑🔬
Experience email the way you want with Mail0 – the first open source email app that puts your privacy and safety first. Join the discord: https://mail0.link/discord
:robot: :speech_balloon: Deep learning for Text to Speech (Discussion forum: https://discourse.mozilla.org/c/tts)
Open-source library of optimized deep learning operations (matmul, convolution, attention) for CPUs (x64, AArch64, RISC-V) and Intel GPUs. Used by PyTorch, TensorFlow, OpenVINO, and ONNX Runtime.
- onednn
- oneapi
- performance
- cpp
A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.
- ai
- fairness-ai
- fairness
- fairness-testing
Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models
- machine-learning
- generative-models
- drug-discovery
- benchmark
Generation of protein sequences and evolutionary alignments via discrete diffusion models
- discrete-diffusion
- generative-model
- multiple-sequence-alignment
- protein-sequences
Music discovery tool that provides recommendations based on selected Lidarr artists, using Spotify or LastFM.
Deep Reinforcement Learning for de-novo Drug Design
- deeplearning
- reinforcement-learning
- cheminformatics
- molecular-modeling
Tensorflow implementation of "Learning Deep Features for Discriminative Localization"
BatchFlow helps you conveniently work with random or sequential batches of your data and define data processing and machine learning workflows even for datasets that do not fit into memory.
- python3
- data-science
- machine-learning
- python
Crop/Weed Field Image Dataset
- dataset
- crop
- paper
- agriculture
LLM for Drug Editing, ICLR 2024
- chatgpt
- conversation
- drug
- drug-discovery
TransformerCPI: Improving compound–protein interaction prediction by sequence-based deep learning with self-attention mechanism and label reversal experiments(BIOINFORMATICS 2020) https://doi.org/10.1093/bioinformatics/btaa524
- self-attention
- compound-protein-interaction
- transformercpi
- structure-free-virtual-sreening
Optimising chemical reactions using machine learning
- chemistry
- machine-learning
- optimization
- bayesian-optimization
We would like to maintain a list of resources which aim to solve molecular docking and other closely related tasks.
- ai-aided-drug-discovery
- awesome
- drug-discovery
- molecular-docking
NeoDTI: Neural integration of neighbor information from a heterogeneous network for discovering new drug-target interactions
- computational-biology
- bioinformatics
- graph-convolution
- deep-learning
Ultra high-performance secp256k1 ECC engine | Python, Node.js, Rust, Go, C#, Swift, Java bindings | CUDA, Metal, OpenCL GPU | ECDSA, Schnorr, FROST, MuSig2, BIP-352 | 15+ platforms
- cryptography
- cuda
- riscv
- secp256k1
Multi-stage Riemannian flow matching for physically valid molecular docking, with GNINA scoring, PoseBusters filtering, CLI inference, and benchmarks.
- alphafold3
- docking
- drug-design
- drug-discovery
Simple and customizable text tokenization gem.
- rubynlp
- ruby
- nlp
- tokenization