Functional Ensemble Distillation

5 June 2022

Papers citing "Functional Ensemble Distillation"

27 / 27 papers shown

Title
Diversity Matters When Learning From Ensembles G. Nam Jongmin Yoon Yoonho Lee Juho Lee UQCV FedML VLM 91 36 0 27 Oct 2021
Personalized Federated Learning with Gaussian Processes Idan Achituve Aviv Shamsian Aviv Navon Gal Chechik Ethan Fetaya FedML 87 104 0 29 Jun 2021
Laplace Redux -- Effortless Bayesian Deep Learning Erik A. Daxberger Agustinus Kristiadi Alexander Immer Runa Eschenhagen Matthias Bauer Philipp Hennig BDL UQCV 221 315 0 28 Jun 2021
What Are Bayesian Neural Network Posteriors Really Like? Pavel Izmailov Sharad Vikram Matthew D. Hoffman A. Wilson UQCV BDL 74 387 0 29 Apr 2021
GP-Tree: A Gaussian Process Classifier for Few-Shot Incremental Learning Idan Achituve Aviv Navon Yochai Yemini Gal Chechik Ethan Fetaya GP 61 34 0 15 Feb 2021
Bayesian Few-Shot Classification with One-vs-Each Pólya-Gamma Augmented Gaussian Processes Jake C. Snell R. Zemel 94 63 0 20 Jul 2020
Language Models are Few-Shot Learners Tom B. Brown Benjamin Mann Nick Ryder Melanie Subbiah Jared Kaplan ... Christopher Berner Sam McCandlish Alec Radford Ilya Sutskever Dario Amodei BDL 901 42,463 0 28 May 2020
Restoration of Fragmentary Babylonian Texts Using Recurrent Neural Networks Ethan Fetaya Yonatan Lifshitz Elad Aaron S. Gordin AI4CE 13 41 0 04 Mar 2020
BatchEnsemble: An Alternative Approach to Efficient Ensemble and Lifelong Learning Yeming Wen Dustin Tran Jimmy Ba OOD FedML UQCV 186 493 0 17 Feb 2020
Hydra: Preserving Ensemble Diversity for Model Distillation Linh-Tam Tran Bastiaan S. Veeling Kevin Roth J. Swiatkowski Joshua V. Dillon Jasper Snoek Stephan Mandt Tim Salimans Sebastian Nowozin Rodolphe Jenatton 75 59 0 14 Jan 2020
Ensemble Distribution Distillation A. Malinin Bruno Mlodozeniec Mark Gales UQCV 94 236 0 30 Apr 2019
Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning Ruqi Zhang Chunyuan Li Jianyi Zhang Changyou Chen A. Wilson BDL 76 279 0 11 Feb 2019
Bayesian Model-Agnostic Meta-Learning Taesup Kim Jaesik Yoon Ousmane Amadou Dia Sungwoong Kim Yoshua Bengio Sungjin Ahn UQCV BDL 299 503 0 11 Jun 2018
Group Normalization Yuxin Wu Kaiming He 247 3,676 0 22 Mar 2018
Predictive Uncertainty Estimation via Prior Networks A. Malinin Mark Gales UD BDL EDL UQCV PER 199 923 0 28 Feb 2018
mixup: Beyond Empirical Risk Minimization Hongyi Zhang Moustapha Cissé Yann N. Dauphin David Lopez-Paz NoLa 316 9,811 0 25 Oct 2017
On Calibration of Modern Neural Networks Chuan Guo Geoff Pleiss Yu Sun Kilian Q. Weinberger UQCV 299 5,877 0 14 Jun 2017
MMD GAN: Towards Deeper Understanding of Moment Matching Network Chun-Liang Li Wei-Cheng Chang Yu Cheng Yiming Yang Barnabás Póczós GAN 66 725 0 24 May 2017
What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision? Alex Kendall Y. Gal BDL OOD UD UQCV PER 362 4,721 0 15 Mar 2017
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.3K 194,510 0 10 Dec 2015
Distilling Model Knowledge George Papamakarios BDL 54 17 0 08 Oct 2015
Bayesian Dark Knowledge Masashi Sugiyama Vivek Rathod R. Garnett Max Welling BDL UQCV 95 259 0 14 Jun 2015
Variational Dropout and the Local Reparameterization Trick Diederik P. Kingma Tim Salimans Max Welling BDL 229 1,517 0 08 Jun 2015
Distilling the Knowledge in a Neural Network Geoffrey E. Hinton Oriol Vinyals J. Dean FedML 367 19,745 0 09 Mar 2015
Generative Moment Matching Networks Yujia Li Kevin Swersky R. Zemel OOD GAN 121 847 0 10 Feb 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 2.1K 150,364 0 22 Dec 2014
MCMC using Hamiltonian dynamics Radford M. Neal 298 3,282 0 09 Jun 2012