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Suite of tools for deploying and training deep learning models using the JVM. Highlights include model import for keras, tensorflow, and onnx/pytorch, a modular and tiny c++ library for running math code and a java based math library on top of the core c++ library. Also includes samediff: a pytorch/tensorflow like library for running deep learn...
g2o: A General Framework for Graph Optimization
Trainable, memory-efficient, and GPU-friendly PyTorch reproduction of AlphaFold 2
library for nonlinear optimization, wrapping many algorithms for global and local, constrained or unconstrained, optimization
Source code of PyGAD, a Python 3 library for building the genetic algorithm and training machine learning algorithms (Keras & PyTorch).
Computational Geometry Unity library with implementations of intersection algorithms, triangulations like delaunay, voronoi diagrams, polygon clipping, bezier curves, ear clipping, convex hulls, mesh simplification, etc
ProtTrans is providing state of the art pretrained language models for proteins. ProtTrans was trained on thousands of GPUs from Summit and hundreds of Google TPUs using Transformers Models.
Official Repository for the Uni-Mol Series Methods
flybrainlabs authority nodes, complete simulation replay, archives, and service APIs.
flybrainlabs native and WebAssembly simulation engines and browser mining.
DNABERT: pre-trained Bidirectional Encoder Representations from Transformers model for DNA-language in genome
RBDL is a C++ library that contains some essential and efficient rigid body dynamics algorithms such as the Articulated Body Algorithm (ABA) for forward dynamics, Recursive Newton-Euler Algorithm (RNEA) for inverse dynamics, the Composite Rigid Body Algorithm (CRBA) for the efficient computation of the joint space inertia matrix and is also able to compute forward dynamics with external contact constraints and collision impulses. Furthermore it has some basic support for forward and inverse kinematics.
U-Net Brain Tumor Segmentation
[ICLR 2024] DNABERT-2: Efficient Foundation Model and Benchmark for Multi-Species Genome
A Python native dynamical system simulation framework in the block diagram paradigm.
Genomic Pretrained Network - GPN, GPN-MSA, PhyloGPN, GPN-Star
Pathology Language and Image Pre-Training (PLIP) is the first vision and language foundation model for Pathology AI (Nature Medicine). PLIP is a large-scale pre-trained model that can be used to extract visual and language features from pathology images and text description. The model is a fine-tuned version of the original CLIP model.
Neural networks toolbox focused on medical image analysis
TriWild: Robust Triangulation with Curve Constraints
Java Constraint Programming solver
Automated 3D cell detection in very large images
A Python interface to access neuroanatomical atlases
Automated 3D brain registration with support for multiple species and atlases.
A Swift port of the Cassowary linear constraint solver