Topic: world-models Goto Github
Some thing interesting about world-models
Some thing interesting about world-models
world-models,Create and test your own cell colonies!
User: anton-mel
Home Page: https://egame.vercel.app/
world-models,PyTorch World Model implementation with PPO.
User: arnaudvl
world-models,Learning Robust Dynamics Through Variational Sparse Gating
User: arnavkj1995
world-models,
Organization: baruda-ai
world-models,Recall to Imagine, a model-based RL algorithm with superhuman memory. Oral (1.2%) @ ICLR 2024
Organization: chandar-lab
Home Page: https://recall2imagine.github.io/
world-models, I GAVE GPT-4 EYES!
User: charmve
world-models,DayDreamer: World Models for Physical Robot Learning
User: danijar
Home Page: https://danijar.com/daydreamer
world-models,Deep Hierarchical Planning from Pixels
User: danijar
Home Page: https://danijar.com/director/
world-models,Dream to Control: Learning Behaviors by Latent Imagination
User: danijar
Home Page: https://danijar.com/dreamer
world-models,Mastering Atari with Discrete World Models
User: danijar
Home Page: https://danijar.com/dreamerv2
world-models,Mastering Diverse Domains through World Models
User: danijar
Home Page: https://danijar.com/dreamerv3
world-models,World Models with A3C on Carracing-v0 in gym
Organization: deepest-project
world-models,World Models applied to the Open AI Sonic Retro Contest
User: dylandjian
world-models,DIAMOND (DIffusion As a Model Of eNvironment Dreams) is a reinforcement learning agent trained in a diffusion world model.
User: eloialonso
Home Page: https://arxiv.org/abs/2405.12399
world-models,Transformers are Sample-Efficient World Models. ICLR 2023, notable top 5%.
User: eloialonso
Home Page: https://openreview.net/forum?id=vhFu1Acb0xb
world-models,Original implementations of the VC-FB and MC-FB algorithms from "Zero-Shot Reinforcement Learning from Low Quality Data" by Jeen et. al (2024).
User: enjeeneer
Home Page: https://enjeeneer.io/projects/zero-shot-rl/
world-models,Pytorch implementation of DreamerV2: Mastering Atari with Discrete World Models, based on the original implementation
User: esteveste
world-models,A curated list of world models for autonomous driving. Keep updated.
User: haoranzhuexplorer
world-models,γε€ζ¨‘ζ倧樑εοΌζ°δΈδ»£δΊΊε·₯ζΊθ½ζζ―θεΌγδ½θ οΌει³οΌζε
User: hcplab-sysu
Home Page: https://hcplab-sysu.github.io/Book-of-MLM/
world-models,VQ-VAE-based image tokenizer for model-based RL
User: howsmyanimeprofilepicture
world-models,Master's thesis project on learning stateful simulations with deep differentiable models. The focus is to train a neural network to simulate a game (PONG) end-to-end.
User: ichko
world-models,Implementation of the paper <Model-based Reinforcement Learning for Predictions and Control for Limit Order Books (Wei et al., J.P. Morgan AI Research, 2019)>.
User: jeonghwan-cheon
world-models,A structured implementation of MuZero
User: johan-gras
world-models,Pytorch Implementation of the World Models paper from 2018.
User: johanngerberding
world-models,Transformer-based World Models
User: jrobine
Home Page: https://arxiv.org/abs/2303.07109
world-models,Clockwork VAEs in JAX/Flax
User: juliuskunze
world-models,Source code for Master's Thesis: Curiosity-driven Planning with Reinforcement Learning.
User: kim-ngu
world-models,[ICLR 2023] Choreographer: a model-based agent that discovers and learns unsupervised skills in latent imagination, and it's able to efficiently coordinate and adapt the skills to solve downstream tasks.
User: mazpie
Home Page: https://skillchoreographer.github.io/
world-models,[NeurIPS 2021] Contrastive learning formulation of the active inference framework, for matching visual goal states.
User: mazpie
Home Page: https://contrastive-aif.github.io/
world-models,[GenRL] Multimodal foundation world models allow grounding language and video prompts into embodied domains, by turning them into sequences of latent world model states. Latent state sequences can be decoded using the decoder of the model, allowing visualization of the expected behavior, before training the agent to execute it.
User: mazpie
Home Page: https://mazpie.github.io/genrl/
world-models,[ICML 2023] Pre-train world model-based agents with different unsupervised strategies, fine-tune the agent's components selectively, and use planning (Dyna-MPC) during fine-tuning.
User: mazpie
Home Page: https://masteringurlb.github.io/
world-models,A reinforcement learning project for crowd-dynamics in a very narrow corridor
User: nima-siboni
world-models,Code for "Planning Goals for Exploration", ICLR2023 Spotlight. An unsupervised RL agent for hard exploration tasks.
Organization: penn-pal-lab
Home Page: https://penn-pal-lab.github.io/peg/
world-models,
User: prakharsingh95
world-models,We develop world models that can be adapted with natural language. Intergrating these models into artificial agents allows humans to effectively control these agents through verbal communication.
Organization: princeton-nlp
Home Page: https://language-guided-world-model.github.io
world-models,Code for the ICLR 2024 spotlight paper: "Learning to Act without Actions" (introducing Latent Action Policies)
User: schmidtdominik
Home Page: https://arxiv.org/abs/2312.10812
world-models,A new version of world models using Echo-state networks and random weight-fixed CNNs
User: shahdsaf
world-models,Jax/Flax Implementation of TD-MPC2
User: shaneflandermeyer
world-models,Flax Implementation of DreamerV3 on Crafter
User: symoon11
world-models,Code release for "HarmonyDream: Task Harmonization Inside World Models" (ICML 2024), https://arxiv.org/abs/2310.00344
Organization: thuml
world-models,World Model based Autonomous Driving Platform in CARLA :car:
Organization: ucd-dare
world-models,Efficient World Models with Context-Aware Tokenization. ICML 2024
User: vmicheli
Home Page: https://arxiv.org/abs/2406.19320
world-models,Toward Multi Modality Language Model - implementation of GPT-4o/Project Astra
User: voidful
world-models,Attempt at reinforcement learning with curiosity for Sonic the Hedgehog games. Number 149 on OpenAI retro contest leaderboard, but more work needed
User: wassname
world-models,Minimum viable reinforcement learning algorithms for your educational convenience.
User: wegfawefgawefg
world-models,Dreamer on JAX
User: yardenas
world-models,Related papers for reinforcement learning, including classic papers and latest papers in top conferences
User: yingchengyang
world-models,[NeurIPS 2022] SGAM: Building a Virtual 3D World through Simultaneous Generation and Mapping
User: yshen47
Home Page: https://yshen47.github.io/sgam/
world-models,A comprehensive survey of forging vision foundation models for autonomous driving, including challenges, methodologies, and opportunities.
User: zhanghm1995
world-models,TrafficBots: Towards World Models for Autonomous Driving Simulation and Motion Prediction. ICRA 2023. You may also want to check out the updated version: https://github.com/zhejz/TrafficBotsV1.5
User: zhejz
Home Page: https://zhejz.github.io/trafficbots
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