| Name | Version | Summary | date |
| medimm |
0.0.8 |
PyTorch Medical 3D Image Models |
2024-11-16 10:39:38 |
| streaming-deep-rl |
0.0.2 |
Streaming Deep Reinforcement Learning |
2024-11-15 15:34:42 |
| q-transformer |
0.2.2 |
Q-Transformer |
2024-11-15 15:20:02 |
| PyTorchLayerViz |
1.2.5 |
PyTorchLayerViz is a Python library that allows you to visualize the weights and feature maps of a PyTorch model. |
2024-11-14 18:40:20 |
| tabm |
0.0.1.dev0 |
TabM. |
2024-11-14 10:47:28 |
| fjformer |
0.0.91 |
Embark on a journey of paralleled/unparalleled computational prowess with FJFormer in JAX |
2024-11-14 10:11:07 |
| ai-lang |
0.0.4 |
DotAI - Natural Language Programming Language |
2024-11-14 00:02:22 |
| werk24 |
1.12.2 |
AI-powered library for extracting engineering data from PDF and image-based technical drawings, automating key detail retrieval for manufacturing workflows. |
2024-11-13 09:11:08 |
| step-kit |
0.2.8 |
STEP, an acronym for Spatial Transcriptomics Embedding Procedure, is a deep learning-based tool for the analysis of single-cell RNA (scRNA-seq) and spatially resolved transcriptomics (SRT) data. STEP introduces a unified approach to process and analyze multiple samples of scRNA-seq data as well as align several sections of SRT data, disregarding location relationships. Furthermore, STEP conducts integrative analysis across different modalities like scRNA-seq and SRT. |
2024-11-13 08:42:33 |
| graforvfl |
1.2.0 |
GrafoRVFL: A Gradient-Free Optimization Framework for Boosting Random Vector Functional Link Network |
2024-11-13 01:53:32 |
| maskbit-pytorch |
0.0.2 |
MaskBit |
2024-11-12 19:18:27 |
| mantra-dataset |
0.0.6 |
A package for working with higher-order datasets like manifold triangulations. |
2024-11-12 16:14:53 |
| triformer |
3.0.7 |
Transformer components in Triton |
2024-11-12 11:35:54 |
| rschip |
0.3.1 |
Prepare satellite images and training data for use with deep learning models |
2024-11-12 11:34:11 |
| opda |
0.7.0 |
Design and analyze optimal deep learning models. |
2024-11-12 05:58:19 |
| rtdl_num_embeddings |
0.0.11 |
On Embeddings for Numerical Features in Tabular Deep Learning. |
2024-11-11 21:34:50 |
| aucurriculum |
0.1.1 |
A Curriculum Learning Toolkit for Deep Learning Tasks built on top of autrainer. |
2024-11-11 17:53:06 |
| batdetect2 |
1.1.1 |
Deep learning model for detecting and classifying bat echolocation calls in high frequency audio recordings. |
2024-11-11 13:03:41 |
| anylabeling |
0.4.15 |
Effortless data labeling with AI support |
2024-11-10 08:19:19 |
| anylabeling-gpu |
0.4.15 |
Effortless data labeling with AI support |
2024-11-10 08:19:10 |