Solving reinforcement learning tasks which require language and vision

Overview

Multimodal Reinforcement Learning

JAX implementations of the following multimodal reinforcement learning approaches.

  • Dual-coding Episodic Memory from "Grounded Language Learning Fast and Slow"

    The goal in this setting is for the agent to be presented with multiple objects with made up names following "This is a _____" statements and to then carry out an instruction such as "Move the wazzle to the table." This task requires the agent to learn long-term language and vision representations for concepts like "This is a" and objects that carry over between episodes such as "table" while also being able to learn one-shot representations of novel objects and their names.

Usage

Start by setting up the environment locally by running

poetry install
poetry shell

The learning environment depends on Docker and requires that the Docker Desktop program is running (on Mac). Once that's done you can run the default environment (fast mapping with 3 objects from the paper).

python fast_slow_learning/main.py
Owner
Henry Prior
I like probability, games, and learning (machine & human)
Henry Prior
AdvStyle - Official PyTorch Implementation

AdvStyle - Official PyTorch Implementation Paper | Supp Discovering Interpretable Latent Space Directions of GANs Beyond Binary Attributes. Huiting Ya

Beryl 37 Oct 21, 2022
Library for converting from RGB / GrayScale image to base64 and back.

Library for converting RGB / Grayscale numpy images from to base64 and back. Installation pip install -U image_to_base_64 Conversion RGB to base 64 b

Vladimir Iglovikov 16 Aug 28, 2022
Repository for benchmarking graph neural networks

Benchmarking Graph Neural Networks Updates Nov 2, 2020 Project based on DGL 0.4.2. See the relevant dependencies defined in the environment yml files

NTU Graph Deep Learning Lab 2k Jan 03, 2023
This demo showcase the use of onnxruntime-rs with a GPU on CUDA 11 to run Bert in a data pipeline with Rust.

Demo BERT ONNX pipeline written in rust This demo showcase the use of onnxruntime-rs with a GPU on CUDA 11 to run Bert in a data pipeline with Rust. R

Xavier Tao 14 Dec 17, 2022
for a paper about leveraging discourse markers for training new models

TSLM-DISCOURSE-MARKERS Scope This repository contains: (1) Code to extract discourse markers from wikipedia (TSA). (1) Code to extract significant dis

International Business Machines 6 Nov 02, 2022
Code for paper "ASAP-Net: Attention and Structure Aware Point Cloud Sequence Segmentation"

ASAP-Net This project implements ASAP-Net of paper ASAP-Net: Attention and Structure Aware Point Cloud Sequence Segmentation (BMVC2020). Overview We i

Hanwen Cao 26 Aug 25, 2022
The official code for PRIMER: Pyramid-based Masked Sentence Pre-training for Multi-document Summarization

PRIMER The official code for PRIMER: Pyramid-based Masked Sentence Pre-training for Multi-document Summarization. PRIMER is a pre-trained model for mu

AI2 111 Dec 18, 2022
CTRMs: Learning to Construct Cooperative Timed Roadmaps for Multi-agent Path Planning in Continuous Spaces

CTRMs: Learning to Construct Cooperative Timed Roadmaps for Multi-agent Path Planning in Continuous Spaces This is a repository for the following pape

17 Oct 13, 2022
Package for working with hypernetworks in PyTorch.

Package for working with hypernetworks in PyTorch.

Christian Henning 71 Jan 05, 2023
Video-based open-world segmentation

UVO_Challenge Team Alpes_runner Solutions This is an official repo for our UVO Challenge solutions for Image/Video-based open-world segmentation. Our

Yuming Du 84 Dec 22, 2022
Understanding the Generalization Benefit of Model Invariance from a Data Perspective

Understanding the Generalization Benefit of Model Invariance from a Data Perspective This is the code for our NeurIPS2021 paper "Understanding the Gen

1 Jan 15, 2022
Pytorch implementation of our paper LIMUSE: LIGHTWEIGHT MULTI-MODAL SPEAKER EXTRACTION.

LiMuSE Overview Pytorch implementation of our paper LIMUSE: LIGHTWEIGHT MULTI-MODAL SPEAKER EXTRACTION. LiMuSE explores group communication on a multi

Auditory Model and Cognitive Computing Lab 17 Oct 26, 2022
Research into Forex price prediction from price history using Deep Sequence Modeling with Stacked LSTMs.

Forex Data Prediction via Recurrent Neural Network Deep Sequence Modeling Research Paper Our research paper can be viewed here Installation Clone the

Alex Taradachuk 2 Aug 07, 2022
Deep Inside Convolutional Networks - This is a caffe implementation to visualize the learnt model

Deep Inside Convolutional Networks This is a caffe implementation to visualize the learnt model. Part of a class project at Georgia Tech Problem State

Jigar 61 Apr 15, 2022
PyTorch code for 'Efficient Single Image Super-Resolution Using Dual Path Connections with Multiple Scale Learning'

Efficient Single Image Super-Resolution Using Dual Path Connections with Multiple Scale Learning This repository is for EMSRDPN introduced in the foll

7 Feb 10, 2022
[NeurIPS-2021] Slow Learning and Fast Inference: Efficient Graph Similarity Computation via Knowledge Distillation

Efficient Graph Similarity Computation - (EGSC) This repo contains the source code and dataset for our paper: Slow Learning and Fast Inference: Effici

24 Dec 31, 2022
Official Pytorch implementation of the paper "MotionCLIP: Exposing Human Motion Generation to CLIP Space"

MotionCLIP Official Pytorch implementation of the paper "MotionCLIP: Exposing Human Motion Generation to CLIP Space". Please visit our webpage for mor

Guy Tevet 173 Dec 26, 2022
Animal Sound Classification (Cats Vrs Dogs Audio Sentiment Classification)

this is a simple artificial neural network model using deep learning and torch-audio to classify cats and dog sounds.

crispengari 3 Dec 05, 2022
Automatically creates genre collections for your Plex media

Plex Auto Genres Plex Auto Genres is a simple script that will add genre collection tags to your media making it much easier to search for genre speci

Shane Israel 63 Dec 31, 2022
Revisiting, benchmarking, and refining Heterogeneous Graph Neural Networks.

Heterogeneous Graph Benchmark Revisiting, benchmarking, and refining Heterogeneous Graph Neural Networks. Roadmap We organize our repo by task, and on

THUDM 176 Dec 17, 2022