MONOTONE OPERATOR EQUILIBRIUM NETWORKS

von Winston, Ezra
Veröffentlicht in NeurIPS (34. : 2020 : Online) 34th Conference on Neural Information Processing Systems (NeurIPS 2020) ; Volume 13 of 27 (2021)

Losses over Labels: Weakly Supervised Learning via Direct Loss Construction

von Sam, Dylan
Veröffentlicht in AAAI Conference on Artificial Intelligence (37. : 2023 : Washington, DC; Online) 37th AAAI Conference on Artificial Intelligence (AAAI-23) ; Volume 8, part 2 of 2 (2023)

LEARNING STABLE DEEP DYNAMICS MODELS

von Kolter, J. Zico
Veröffentlicht in NeurIPS (33. : 2019 : Vancouver, British Columbia) 32nd Conference on Neural Information Processing Systems (NeurIPS 2019) ; Volume 14 of 20 (2020)

The Pitfalls of Regularization in Off-Policy TD Learning

von Manek, Gaurav
Veröffentlicht in NeurIPS (36. : 2022 : New Orleans, La.; Online) 36th Conference on Neural Information Processing Systems (NeurIPS 2022 ; Volume 46 of 50 (2023)

UNIFORM CONVERGENCE MAY BE UNABLE TO EXPLAIN GENERALIZATION IN DEEP LEARNING

von Nagarajan, Vaishnavh
Veröffentlicht in NeurIPS (33. : 2019 : Vancouver, British Columbia) 32nd Conference on Neural Information Processing Systems (NeurIPS 2019) ; Volume 15 of 20 (2020)

COMMUNITY DETECTION USING FAST LOW-CARDINALITY SEMIDEFINITE PROGRAMMING?

von Wang, Po-Wei
Veröffentlicht in NeurIPS (34. : 2020 : Online) 34th Conference on Neural Information Processing Systems (NeurIPS 2020) ; Volume 5 of 27 (2021)

Deep Equilibrium Approaches to Diffusion Models

von Pokle, Ashwini
Veröffentlicht in NeurIPS (36. : 2022 : New Orleans, La.; Online) 36th Conference on Neural Information Processing Systems (NeurIPS 2022 ; Volume 49 of 50 (2023)

STABILIZING EQUILIBRIUM MODELS BY JACOBIAN REGULARIZATION

von BAI, SHAOJIE
Veröffentlicht in International Conference on Machine Learning (38. : 2021 : Online) International Conference on Machine Learning (ICML 2021 ; Part 1 of 16 (2022)

(Implicit)2: Implicit Layers for Implicit Representations

von Huang, Zhichun
Veröffentlicht in NeurIPS (35. : 2021 : Online) 35th Conference on Neural Information Processing Systems (NeurIPS 2021) ; Volume 12 of 36 (2022)

ADVERSARIAL ROBUSTNESS AGAINST THE UNION OF MULTIPLE PERTURBATION MODELS

von Maini, Pratyush
Veröffentlicht in International Conference on Machine Learning (37. : 2020 : Online) 37th International Conference on Machine Learning (ICML 2020) ; Part 9 of 15 (2021)

DEEP EQUILIBRIUM MODELS

von Bai, Shaojie
Veröffentlicht in NeurIPS (33. : 2019 : Vancouver, British Columbia) 32nd Conference on Neural Information Processing Systems (NeurIPS 2019) ; Volume 1 of 20 (2020)

OVERFITTING IN ADVERSARIALLY ROBUST DEEP LEARNING

von Rice, Leslie
Veröffentlicht in International Conference on Machine Learning (37. : 2020 : Online) 37th International Conference on Machine Learning (ICML 2020) ; Part 11 of 15 (2021)

OVERFITTING IN ADVERSARIALLY ROBUST DEEP LEARNING

von Rice, Leslie
Veröffentlicht in International Conference on Machine Learning (37. : 2020 : Online) 37th International Conference on Machine Learning (ICML 2020) ; Part 11 of 15 (2021)

MULTISCALE DEEP EQUILIBRIUM MODELS

von Bai, Shaojie
Veröffentlicht in NeurIPS (34. : 2020 : Online) 34th Conference on Neural Information Processing Systems (NeurIPS 2020) ; Volume 7 of 27 (2021)

Deep Archimedean Copulas

von Ling, Chun Kai
Veröffentlicht in NeurIPS (34. : 2020 : Online) 34th Conference on Neural Information Processing Systems (NeurIPS 2020) ; Volume 3 of 27 (2021)

Efficient semidefinite-programming-based inference for binary and multi-class MRFs

von Pabbaraju, Chirag
Veröffentlicht in NeurIPS (34. : 2020 : Online) 34th Conference on Neural Information Processing Systems (NeurIPS 2020) ; Volume 6 of 27 (2021)

DORO: DISTRIBUTIONAL AND OUTLIER ROBUST OPTIMIZATION

von ZHAI, RUNTIAN
Veröffentlicht in International Conference on Machine Learning (38. : 2021 : Online) International Conference on Machine Learning (ICML 2021 ; Part 16 of 16 (2022)

Robustness between the worst and average case

von Rice, Leslie
Veröffentlicht in NeurIPS (35. : 2021 : Online) 35th Conference on Neural Information Processing Systems (NeurIPS 2021) ; Volume 33 of 36 (2022)

Joint inference and input optimization in equilibrium networks

von Gurumurthy, Swaminathan
Veröffentlicht in NeurIPS (35. : 2021 : Online) 35th Conference on Neural Information Processing Systems (NeurIPS 2021) ; Volume 20 of 36 (2022)

Agreement-on-the-line: Predicting the Performance of Neural Networks under Distribution Shift

von Baek, Christina
Veröffentlicht in NeurIPS (36. : 2022 : New Orleans, La.; Online) 36th Conference on Neural Information Processing Systems (NeurIPS 2022 ; Volume 25 of 50 (2023)