ZacharyZekaiXu

ZacharyZekaiXu's Stars

• TomGeorge1234/STDP-SR

  We study place and grid cells of an RL agent learns successor representations (SR) in compositional mazes.

  Language:Jupyter Notebook92

• juliancervos/stdp-nmnist

  Repository for the master thesis titled "Local Unsupervised Learning of Multimodal Event-Based Data with Spiking Neural Networks", by Julian Lopez Gordillo (MSc in Artificial Intelligence, 2019-2021).

  Language:Python215

• matthewvowels1/Awesome-VAEs

  A curated list of awesome work on VAEs, disentanglement, representation learning, and generative models.

  77977

• daifengwanglab/scMNC

  Language:Jupyter Notebook21

• natashamjaques/MultimodalAutoencoder

  Code supporting the paper "Multimodal Autoencoder: A Deep Learning Approach to Filling In Missing Sensor Data and Enabling Better Mood Prediction"

  Language:Python7230

• jhuebotter/SpikingVAE

  Master Thesis Project of Justus Hübotter

  Language:Jupyter Notebook111

• BrainsOnBoard/paper_RPEs_in_drosophila_mb

  Code and data for the manuscript "Learning with reinforcement prediction errors in a model of the Drosophila mushroom body".

  Language:MATLAB3

• amrzv/awesome-colab-notebooks

  Collection of google colaboratory notebooks for fast and easy experiments

  Language:Python1.3k245

• mehmetfdemirel/PolycrystalGraph

  Code base for the graph neural network-based polygrain microstructure property prediction project

  Language:Python3718

• clear-nus/TactileSGNet

  A spiking graph neural network for event-based learning

  Language:Python466

• xingyul/flownet3d

  FlowNet3D: Learning Scene Flow in 3D Point Clouds (CVPR 2019)

  Language:Python35983

• MaxChanger/awesome-point-cloud-scene-flow

  A list of point cloud scene flow papers, codes and datasets.

  19414

• SMohammadi89/PointView-GCN

  The code and dataset will be available soon here

  Language:Python5515

• ricardodeazambuja/IJCNN2017

  Short-Term Plasticity in a Liquid State Machine Biomimetic Robot Arm Controller

  Language:Jupyter Notebook6

• ricardodeazambuja/Bee

  The Spiking Reservoir (Liquid State Machine - LSM) Simulator

  Language:Jupyter Notebook4910

• guillaume-chevalier/Spiking-Neural-Network-SNN-with-PyTorch-where-Backpropagation-engenders-STDP

  What about coding a Spiking Neural Network using an automatic differentiation framework? In SNNs, there is a time axis and the neural network sees data throughout time, and activation functions are instead spikes that are raised past a certain pre-activation threshold. Pre-activation values constantly fades if neurons aren't excited enough.

  Language:Jupyter Notebook25749

• ZulunZhu/SpikingGCN

  Language:Jupyter Notebook399

• IGITUGraz/MemoryDependentComputation

  Code for Limbacher, T., Özdenizci, O., & Legenstein, R. (2022). Memory-enriched computation and learning in spiking neural networks through Hebbian plasticity. arXiv preprint arXiv:2205.11276.

  Language:Python63

• kamata1729/FullySpikingVAE

  Official implementation of Fully Spiking Variational Autoencoder [AAAI2022]

  Language:Python6623

• google-deepmind/3d-shapes

  This repository contains the 3D shapes dataset, used in Kim, Hyunjik and Mnih, Andriy. "Disentangling by Factorising." In Proceedings of the 35th International Conference on Machine Learning (ICML). 2018. to assess the disentanglement properties of unsupervised learning methods.

  Language:Jupyter Notebook12631

• rhgao/ObjectFolder

  ObjectFolder Dataset

  Language:Python14810

• event-driven-robotics/tactile_braille_reading

  Language:Jupyter Notebook105

• neural-reckoning/cosyne-tutorial-2022

  Cosyne workshop tutorial 2022

  Language:Jupyter Notebook10430

• comob-project/snn-sound-localization

  Training spiking neural networks for sound localization

  Language:Jupyter Notebook6026

• alberto-antonietti/paper_whisking

  Code related to the paper: "Brain-inspired spiking neural network controller for a neurorobotic whisker system": https://doi.org/10.3389/fnbot.2022.817948

  Language:Jupyter Notebook2

• clear-nus/VT_SNN

  VT-SNN

  Language:Python249

• annkennedy/mushroomBody

  Code for simulating and analyzing the spiking mushroom body model

  Language:MATLAB42

• gyyang/nn-brain

  Tutorial codes for modeling brains with neural nets

  Language:Jupyter Notebook20663

• facebookresearch/3D-Vision-and-Touch

  When told to understand the shape of a new object, the most instinctual approach is to pick it up and inspect it with your hand and eyes in tandem. Here, touch provides high fidelity localized information while vision provides complementary global context. However, in 3D shape reconstruction, the complementary fusion of visual and haptic modalities remains largely unexplored. In this paper, we study this problem and present an effective chart-based approach to fusing vision and touch, which leverages advances in graph convolutional networks. To do so, we introduce a dataset of simulated touch and vision signals from the interaction between a robotic hand and a large array of 3D objects. Our results show that (1) leveraging both vision and touch signals consistently improves single-modality baselines, especially when the object is occluded by the hand touching it; (2) our approach outperforms alternative modality fusion methods and strongly benefits from the proposed chart-based structure; (3) reconstruction quality boosts with the number of grasps provided; and (4) the touch information not only enhances the reconstruction at the touch site but also extrapolates to its local neighborhood.

  Language:Python6814

• facebookresearch/Active-3D-Vision-and-Touch

  A repository for the paper Active 3D Shape Reconstruction from Vision and Touch and robotic touch simulator package.

  Language:Jupyter Notebook249