aklein1995

aklein1995's Stars

• open-mmlab/mmdetection

  OpenMMLab Detection Toolbox and Benchmark

  Language:Python29.1k3688.3k9.4k

• haotian-liu/LLaVA

  [NeurIPS'23 Oral] Visual Instruction Tuning (LLaVA) built towards GPT-4V level capabilities and beyond.

  Language:Python19.3k1581.5k2.1k

• marcotcr/lime

  Lime: Explaining the predictions of any machine learning classifier

  Language:JavaScript11.5k2636341.8k

• hoya012/deep_learning_object_detection

  A paper list of object detection using deep learning.

  Language:Python11.3k622272.8k

• alshedivat/al-folio

  A beautiful, simple, clean, and responsive Jekyll theme for academics

  Language:HTML10.5k2454810.9k

• mlfoundations/open_clip

  An open source implementation of CLIP.

  Language:Python9.8k77466951

• pytorch/captum

  Model interpretability and understanding for PyTorch

  Language:Python4.8k267538487

• uzh-rpg/flightmare

  An Open Flexible Quadrotor Simulator

  Language:C++98032168342

• google-deepmind/open_x_embodiment

  Language:Jupyter Notebook775177155

• hila-chefer/Transformer-MM-Explainability

  [ICCV 2021- Oral] Official PyTorch implementation for Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers, a novel method to visualize any Transformer-based network. Including examples for DETR, VQA.

  Language:Jupyter Notebook774835106

• mila-iqia/babyai

  BabyAI platform. A testbed for training agents to understand and execute language commands.

  Language:Python6873646144

• uzh-rpg/agile_autonomy

  Repository Containing the Code associated with the Paper: "Learning High-Speed Flight in the Wild"

  Language:C++5841593164

• yihaosun1124/OfflineRL-Kit

  An elegant PyTorch offline reinforcement learning library for researchers.

  Language:Python25961132

• PaddlePaddle/InterpretDL

  InterpretDL: Interpretation of Deep Learning Models，基于『飞桨』的模型可解释性算法库。

  Language:Python235114138

• flowersteam/Grounding_LLMs_with_online_RL

  We perform functional grounding of LLMs' knowledge in BabyAI-Text

  Language:Python21372224

• bennylp/RL-Taxonomy

  Loose taxonomy of reinforcement learning algorithms

  Language:Python1507012

• rigvedrs/YOLO-V8-CAM

  Wanna know what your model sees? Here's a package for applying EigenCAM on the new YOLO V8 model

  Language:Jupyter Notebook11612121

• imgeorgiev/DiffRL

  Learning Optimal Policies Through Contact in Differentiable Simulation

  Language:Jupyter Notebook80108

• jahongir7174/YOLOv8-qat

  Quantization Aware Training

  Language:Python52068

• hungntt/xai_thyroid

  Classification and Object Detection XAI methods (CAM-based, backpropagation-based, perturbation-based, statistic-based) for thyroid cancer ultrasound images

  Language:Python49227

• hysts/pytorch_D-RISE

  A PyTorch implementation of D-RISE

  Language:Jupyter Notebook370213

• jvadillo/curso-django-paso-a-paso

  Curso de desarrollo de aplicaciones web con Django paso a paso

  346021

• facebookresearch/gen_dgrl

  Official codebase for "The Generalization Gap in Offline Reinforcement Learning" accepted to ICLR 2024

  Language:Python26314

• Jaewoopudding/GTA

  Official codebase for GTA: Generative Trajectory Augmentation with Guidance for Offline Reinforcement Learning.

  Language:Python10102

• Kitware/nrtk

  The Natural Robustness Toolkit (NRTK) is an open source toolkit for generating operationally-realistic perturbations to evaluate the natural robustness of computer vision algorithms.

  Language:Python8523

• fuyw/FuRL

  Language:Python60

• negvet/feature_drift

  Observation of internal feature drift of object detection models (using eXplainable AI (XAI))

  Language:Python60

• WindQingYang/MFPP

  Language:Jupyter Notebook6120

• arya-h/TFM_RL_UPM

  Language:Jupyter Notebook1

• HongBo713/Simple-Vision-Transformer

  A simple implementation for basic ViT

  Language:Jupyter Notebook1