Showing 1 - 20 results of 27 for search 'NeurIPS', query time: 0.15s Refine Results
  1. 1
    On the fairness of disentangled representations

    On the fairness of disentangled representations by Locatello, F, Abbati, G, Rainforth, T, Bauer, S, Schölkopf, B, Bachem, O

    Published 2019
    “…NeurIPS…”
    Conference item
  2. 2
    Labelling unlabelled videos from scratch with multi-modal self-supervision

    Labelling unlabelled videos from scratch with multi-modal self-supervision by Asano, YM, Patrick, M, Rupprecht, C, Vedaldi, A

    Published 2020
    “…NeurIPS…”
    Conference item
  3. 3
    Occluded video instance segmentation: dataset and challenge

    Occluded video instance segmentation: dataset and challenge by Qi, J, Gao, Y, Hu, Y, Wang, X, Liu, X, Bai, X, Belongie, S, Yuille, A, Torr, P, Bai, S

    Published 2021
    “…NeurIPS…”
    Conference item
  4. 4
    Coherent hierarchical multi-label classification networks

    Coherent hierarchical multi-label classification networks by Giunchiglia, E, Lukasiewicz, T

    Published 2020
    “…NeurIPS…”
    Conference item
  5. 5
    Optimal convergence rate for exact policy mirror descent in discounted Markov decision processes

    Optimal convergence rate for exact policy mirror descent in discounted Markov decision processes by Johnson, E, Pike-Burke, C, Rebeschini, P

    Published 2023
    “…NeurIPS…”
    Conference item
  6. 6
    PASS: An ImageNet replacement for self-supervised pretraining without humans

    PASS: An ImageNet replacement for self-supervised pretraining without humans by Asano, YM, Rupprecht, C, Zisserman, A, Vedaldi, A

    Published 2021
    “…NeurIPS…”
    Conference item
  7. 7
    FACMAC: Factored multi−agent centralised policy gradients

    FACMAC: Factored multi−agent centralised policy gradients by Peng, B, Rashid, T, Schroeder de Witt, CA, Kamienny, P-A, Torr, PHS, Böhmer, W, Whiteson, S

    Published 2022
    “…NeurIPS…”
    Conference item
  8. 8
    Regularized Softmax Deep Multi−Agent Q−Learning

    Regularized Softmax Deep Multi−Agent Q−Learning by Pan, L, Rashid, T, Peng, B, Huang, L, Whiteson, S

    Published 2022
    “…NeurIPS…”
    Conference item
  9. 9
    Weighted QMIX: Expanding monotonic value function factorisation for deep multi−agent reinforcement learning

    Weighted QMIX: Expanding monotonic value function factorisation for deep multi−agent reinforcement learning by Rashid, T, Farquhar, G, Peng, B, Whiteson, S

    Published 2020
    “…NeurIPS…”
    Conference item
  10. 10
    ReMaX: relaxing for better training on efficient panoptic segmentation

    ReMaX: relaxing for better training on efficient panoptic segmentation by Sun, S, Wang, W, Yu, Q, Howard, A, Torr, P, Chen, L-C

    Published 2023
    “…NeurIPS…”
    Conference item
  11. 11
    Bayesian Bellman operators

    Bayesian Bellman operators by Fellows, M, Hartikainen, K, Whiteson, S

    Published 2022
    “…NeurIPS…”
    Conference item
  12. 12
    Lightweight generative adversarial networks for text-guided image manipulation

    Lightweight generative adversarial networks for text-guided image manipulation by Li, B, Qi, X, Torr, PHS, Lukasiewicz, T

    Published 2020
    “…NeurIPS…”
    Conference item
  13. 13
    Can Q-learning with graph networks learn a generalizable branching heuristic for a SAT solver?

    Can Q-learning with graph networks learn a generalizable branching heuristic for a SAT solver? by Kurin, V, Godil, S, Whiteson, S, Catanzaro, B

    Published 2020
    “…NeurIPS…”
    Conference item
  14. 14
    A data integration pipeline towards reliable monitoring of phytoplankton and early detection of harmful algal blooms

    A data integration pipeline towards reliable monitoring of phytoplankton and early detection of harmful algal blooms by Guterres, B, Khalid, S, Pias, M, Botelho, S

    Published 2022
    “…NeurIPS…”
    Conference item
  15. 15
    Learning retrospective knowledge with reverse reinforcement learning

    Learning retrospective knowledge with reverse reinforcement learning by Zhang, S, Veeriah, V, Whiteson, S

    Published 2020
    “…NeurIPS…”
    Conference item
  16. 16
    Quantifying learnability and describability of visual concepts emerging in representation learning

    Quantifying learnability and describability of visual concepts emerging in representation learning by Laina, I, Fong, RC, Vedaldi, A

    Published 2020
    “…NeurIPS…”
    Conference item
  17. 17
    Are vision transformers always more robust than convolutional neural networks?

    Are vision transformers always more robust than convolutional neural networks? by Pinto, F, Torr, P, Dokania, PK

    Published 2021
    “…NeurIPS…”
    Conference item
  18. 18
    3D Multi-bodies: fitting sets of plausible 3D human models to ambiguous image data

    3D Multi-bodies: fitting sets of plausible 3D human models to ambiguous image data by Biggs, B, Ehrhardt, S, Joo, H, Graham, B, Vedaldi, A, Novotny, D

    Published 2020
    “…NeurIPS…”
    Conference item
  19. 19
    BoxE: A box embedding model for knowledge base completion

    BoxE: A box embedding model for knowledge base completion by Abboud, R, Ceylan, II, Lukasiewicz, T, Salvatori, T

    Published 2020
    “…NeurIPS…”
    Conference item
  20. 20
    Segmenting moving objects via an object-centric layered representation

    Segmenting moving objects via an object-centric layered representation by Xie, J, Xie, W, Zisserman, A

    Published 2022
    “…NeurIPS…”
    Conference item

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