tp030ny

tp030ny's Stars

• openai/CLIP

  CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image

  Language:Jupyter Notebook25k3243953.2k

• assafelovic/gpt-researcher

  LLM based autonomous agent that does online comprehensive research on any given topic

  Language:Python14.3k1163421.9k

• facebookresearch/esm

  Evolutionary Scale Modeling (esm): Pretrained language models for proteins

  Language:Python3.2k64320627

• BindsNET/bindsnet

  Simulation of spiking neural networks (SNNs) using PyTorch.

  Language:Python1.5k43237331

• amirhossein-kz/Awesome-Diffusion-Models-in-Medical-Imaging

  Diffusion Models in Medical Imaging (Published in Medical Image Analysis Journal)

  1.4k387140

• zhirongw/lemniscate.pytorch

  Unsupervised Feature Learning via Non-parametric Instance Discrimination

  Language:Python7461229134

• NeuromorphicProcessorProject/snn_toolbox

  Toolbox for converting analog to spiking neural networks (ANN to SNN), and running them in a spiking neuron simulator.

  Language:Python36016127105

• Stonesjtu/Pytorch-NCE

  The Noise Contrastive Estimation for softmax output written in Pytorch

  Language:Python31871446

• XDUSPONGE/SNN_benchmark

  24912054

• back8/github_huanghyw_jd_seckill

  Language:Python210291

• marcellacornia/sam

  Predicting Human Eye Fixations via an LSTM-based Saliency Attentive Model. IEEE Transactions on Image Processing (2018)

  Language:Python208104576

• yjwu17/STBP-for-training-SpikingNN

  Spatio-temporal BP for SNNs

  Language:Python2066548

• bcmi/Awesome-Weak-Shot-Learning

  A curated list of papers, code and resources pertaining to weak-shot classification, detection, and segmentation.

  18413113

• yfguo91/Awesome-Spiking-Neural-Networks

  Awesome Spiking Neural Networks

  925010

• alibaba/LucaProt

  LucaProt: A novel deep learning framework that incorporates protein amino acid sequence and structural information to predict protein function.

  Language:Python634315

• putshua/SNN_conversion_QCFS

  Language:Python4811316

• DingJianhao/OptSNNConvertion-RNL-RIL

  Language:Python28026

• ppppps/ANN2SNNConversion_SNM_NeuronNorm

  Pytorch Implementation of Signed Neuron with Memory: Towards Simple, Accurate and High-Efficient ANN-SNN Conversion, IJCAI 2022

  Language:Python22153

• hzc1208/ANN2SNN_SRP

  Language:Python21214

• googlebaba/StableGNN

  StableGNN-Generalizing Graph Neural Networks on Out-Of-Distribution Graphs

  Language:Python18323

• Jiankun-chen/Supervised-SNN-with-GD

  A supervised learning algorithm of SNN is proposed by using spike sequences with complex spatio-temporal information. We explore an error back-propagation method of SNN based on gradient descent. The chain rule proved mathematically that it is sufficient to update the SNN’s synaptic weights by directly using an optimizer. Utilizing the TensorFlow framework, a bilayer supervised learning SNN is constructed from scratch. We take the lead in the application of SAR image classification and conduct experiments on the MSTAR dataset.

  Language:Python18113

• macwiatrak/GeneBac

  GeneBac: a modular framework for predicting antibiotic resistance from DNA sequence.

  Language:Python8100

• jonahanton/SSL_medicalimaging

  Codebase for Imperial MSc AI Group Project: How Well Do Self-Supervised Models Transfer to Medical Imaging?

  Language:Jupyter Notebook5105

• jainpulkit54/metric_learning_siamese_contrastive_loss

  Language:Python40

• Lyu6PosHao/spikingjelly_ann2snn_dev

  SpikingJelly is an open-source deep learning framework for Spiking Neural Network (SNN) based on PyTorch.

  Language:Python2001

• anmolshkl/Word-Vectors-Using-Skip-Grams-and-NCE-Loss

  A Skip Gram model based on NCE loss function for learning word representations

  Language:Python1100

• rat-h/pyneuronautofit

  A set of tools for fitting single- or multi-compartment neuron models parameters, using NSGA2 or Krayzman's dynamically weighted multi-objective optimization

  Language:Python12

• tp030ny/IF_toolbox

  Fit stochastic IF model with spike-triggered current eta and moving threshold gamma as described in: "Parameter extraction and classification of three cortical neuron types reveals two distinct adaptation mechanisms"

  Language:MATLAB1000

• tp030ny/NEUROFIT

  NEUROFIT is a program that fits Hodgkin-Huxley models to voltage-clamp data.

  Language:C1000

• tp030ny/positional_cl

  code for paper Positional Contrastive Learning for Volumetric Medical Image Segmentation

  Language:Python1000