Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter | Paper Citation Record

Observation d341446e-cca0-452a-b1c1-941845a33a78 · outbound

This paper cites Bellemare.

Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter Bellemare

Reference 1

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Observation fc73432c-ae36-463e-937d-8f730845ffa6 · outbound

This paper cites Self-supervised learning from images with a joint-embedding predictive architecture.

Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter Self-supervised learning from images with a joint-embedding predictive architecture

Reference 2

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This paper cites PonderNet: Learning to Ponder.

Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter PonderNet: Learning to Ponder

Reference 3

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This paper cites VICReg : Variance-invariance-covariance regularization for self-supervised learning.

Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter VICReg : Variance-invariance-covariance regularization for self-supervised learning

Reference 4

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This paper cites Adaptive neural networks for efficient inference.

Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter Adaptive neural networks for efficient inference

Reference 6

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This paper cites Exploring simple siamese representation learning.

Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter Exploring simple siamese representation learning

Reference 7

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This paper cites Deep reinforcement learning in a handful of trials using probabilistic dynamics models.

Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter Deep reinforcement learning in a handful of trials using probabilistic dynamics models

Reference 8

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This paper cites Universal transformers.

Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter Universal transformers

Reference 9

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Observation 594b658d-77fd-4f9a-90d2-1da0b530823a · outbound

This paper cites Depth-adaptive transformer.

Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter Depth-adaptive transformer

Reference 10

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This paper cites Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity.

Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity

Reference 11

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This paper cites Collins, Yukun Zhu, Li Zhang, Jonathan Huang, Dmitry Vetrov, and Ruslan Salakhutdinov.

Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter Collins, Yukun Zhu, Li Zhang, Jonathan Huang, Dmitry Vetrov, and Ruslan Salakhutdinov

Reference 12

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Observation 12263de6-9ff4-4dbe-8b31-32f8179ae03d · outbound

This paper cites Bellemare.

Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter Bellemare

Reference 13

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This paper cites Richemond, Elena Buchatskaya, Carl Doersch, Bernardo Avila Pires, Zhaohan Daniel Guo, Mohammad Gheshlaghi Azar, Bilal Piot, Koray Kavukcuoglu, R \'e mi Munos, and Michal Valko.

Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter Richemond, Elena Buchatskaya, Carl Doersch, Bernardo Avila Pires, Zhaohan Daniel Guo, Mohammad Gheshlaghi Azar, Bilal Piot, Koray Kavukcuoglu, R \'e mi Munos, and Michal Valko

Reference 15

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Observation b43f7cad-de0d-4735-be75-81e3e8437970 · outbound

This paper cites Recurrent world models facilitate policy evolution.

Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter Recurrent world models facilitate policy evolution

Reference 16

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Observation 766fd957-96d9-497c-8420-0687ab3a0711 · outbound

This paper cites Learning latent dynamics for planning from pixels.

Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter Learning latent dynamics for planning from pixels

Reference 17

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This paper cites Dream to control: Learning behaviors by latent imagination.

Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter Dream to control: Learning behaviors by latent imagination

Reference 18

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This paper cites Dynamic neural networks: A survey.

Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter Dynamic neural networks: A survey

Reference 20

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This paper cites Temporal difference learning for model predictive control.

Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter Temporal difference learning for model predictive control

Reference 21

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This paper cites TD-MPC2 : Scalable, robust world models for continuous control.

Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter TD-MPC2 : Scalable, robust world models for continuous control

Reference 22

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This paper cites Deep reinforcement learning that matters.

Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter Deep reinforcement learning that matters

Reference 23

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This paper cites When to trust your model: Model-based policy optimization.

Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter When to trust your model: Model-based policy optimization

Reference 25

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This paper cites Kingma and Jimmy Ba.

Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter Kingma and Jimmy Ba

Reference 26

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Observation 7f152bf0-8bb3-45df-b913-43d5a3e99c88 · outbound

This paper cites A path towards autonomous machine intelligence.

Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter A path towards autonomous machine intelligence

Reference 27

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This paper cites Deeply-supervised nets.

Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter Deeply-supervised nets

Reference 28

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This paper cites Decoupled weight decay regularization.

Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter Decoupled weight decay regularization

Reference 29

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This paper cites Mastering Atari , Go , chess and shogi by planning with a learned model.

Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter Mastering Atari , Go , chess and shogi by planning with a learned model

Reference 31

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This paper cites Confident adaptive language modeling.

Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter Confident adaptive language modeling

Reference 32

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This paper cites Devon Hjelm, Aaron Courville, and Philip Bachman.

Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter Devon Hjelm, Aaron Courville, and Philip Bachman

Reference 33

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This paper cites Outrageously large neural networks: The sparsely-gated mixture-of-experts layer.

Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter Outrageously large neural networks: The sparsely-gated mixture-of-experts layer

Reference 34

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Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter Going deeper with convolutions

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This paper cites DeepMind Control Suite.

Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter DeepMind Control Suite

Reference 36

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Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter Unresolved cited work

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Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter MuJoCo : A physics engine for model-based control

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Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter Adaptive Computation Time for Recurrent Neural Networks

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Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter Unresolved cited work

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Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , year=

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Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter International Conference on Learning Representations (ICLR) , year=

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Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter International Conference on Learning Representations (ICLR) , year=

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Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter Advances in Neural Information Processing Systems (NeurIPS) , year=

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Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter Mixture-of-Depths: Dynamically allocating compute in transformer-based language models

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Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter International Conference on Learning Representations (ICLR) , year=

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Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter Journal of Machine Learning Research (JMLR) , volume=

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Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) , year=

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Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter International Conference on Machine Learning (ICML) , year=

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Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter Advances in Neural Information Processing Systems (NeurIPS) , year=

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Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter International Conference on Machine Learning (ICML) , year=

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Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter International Conference on Learning Representations (ICLR) , year=

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Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter Mastering Diverse Domains through World Models

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Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter International Conference on Machine Learning (ICML) , year=

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Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter Unresolved cited work

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Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter Mastering

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Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter Advances in Neural Information Processing Systems (NeurIPS) , year=

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Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter Advances in Neural Information Processing Systems (NeurIPS) , year=

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Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter Open Review preprint (version 0.9.2) , year=

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Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , year=

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Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter Revisiting Feature Prediction for Learning Visual Representations from Video

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Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter Advances in Neural Information Processing Systems (NeurIPS) , year=

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Adaptive Compute in Latent World Models: When Depth Helps, Hurts, or Doesn't Matter IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , year=

Reference 64

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