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Sparsely Changing Latent States for Prediction and Planning in Partially
  Observable Domains
v1v2 (latest)

Sparsely Changing Latent States for Prediction and Planning in Partially Observable Domains

Neural Information Processing Systems (NeurIPS), 2021
29 October 2021
Christian Gumbsch
Martin Volker Butz
Georg Martius
    AI4CE
ArXiv (abs)PDFHTML

Papers citing "Sparsely Changing Latent States for Prediction and Planning in Partially Observable Domains"

8 / 8 papers shown
Dynamic Sparsity: Challenging Common Sparsity Assumptions for Learning World Models in Robotic Reinforcement Learning Benchmarks
Dynamic Sparsity: Challenging Common Sparsity Assumptions for Learning World Models in Robotic Reinforcement Learning Benchmarks
Muthukumar Pandaram
Jakob J. Hollenstein
David Drexel
Samuele Tosatto
A. Rodríguez-Sánchez
J. Piater
CML
200
0
0
11 Nov 2025
Minigrid & Miniworld: Modular & Customizable Reinforcement Learning
  Environments for Goal-Oriented Tasks
Minigrid & Miniworld: Modular & Customizable Reinforcement Learning Environments for Goal-Oriented TasksNeural Information Processing Systems (NeurIPS), 2023
Maxime Chevalier-Boisvert
Bolun Dai
Mark Towers
Rodrigo de Lazcano
Lucas Willems
Salem Lahlou
Suman Pal
Pablo Samuel Castro
Jordan Terry
VGen
348
307
0
24 Jun 2023
Object-Centric Learning for Real-World Videos by Predicting Temporal
  Feature Similarities
Object-Centric Learning for Real-World Videos by Predicting Temporal Feature SimilaritiesNeural Information Processing Systems (NeurIPS), 2023
Antonios Tragoudaras
Maximilian Seitzer
Georg Martius
OCL
435
62
0
07 Jun 2023
Inductive biases in deep learning models for weather prediction
Inductive biases in deep learning models for weather prediction
Jannik Thümmel
Matthias Karlbauer
S. Otte
C. Zarfl
Georg Martius
...
Thomas Scholten
Ulrich Friedrich
V. Wulfmeyer
B. Goswami
Martin Volker Butz
AI4CE
299
8
0
06 Apr 2023
World Models and Predictive Coding for Cognitive and Developmental
  Robotics: Frontiers and Challenges
World Models and Predictive Coding for Cognitive and Developmental Robotics: Frontiers and Challenges
T. Taniguchi
Shingo Murata
Masahiro Suzuki
D. Ognibene
Pablo Lanillos
...
L. Jamone
Tomoaki Nakamura
Alejandra Ciria
B. Lara
G. Pezzulo
268
73
0
14 Jan 2023
Developing hierarchical anticipations via neural network-based event
  segmentation
Developing hierarchical anticipations via neural network-based event segmentationInternational Conference on Development and Learning (ICDL), 2022
Christian Gumbsch
M. Adam
B. Elsner
Georg Martius
Martin Volker Butz
158
6
0
04 Jun 2022
Learning What and Where: Disentangling Location and Identity Tracking
  Without Supervision
Learning What and Where: Disentangling Location and Identity Tracking Without SupervisionInternational Conference on Learning Representations (ICLR), 2022
Manuel Traub
S. Otte
Tobias Menge
Matthias Karlbauer
Jannik Thummel
Martin Volker Butz
394
22
0
26 May 2022
Towards Continual Reinforcement Learning: A Review and Perspectives
Towards Continual Reinforcement Learning: A Review and PerspectivesJournal of Artificial Intelligence Research (JAIR), 2020
Khimya Khetarpal
Matthew D Riemer
Irina Rish
Doina Precup
CLLOffRL
555
376
0
25 Dec 2020
1