Extremely Simple Activation Shaping for Out-of-Distribution Detection

Extremely Simple Activation Shaping for Out-of-Distribution Detection

20 September 2022

Andrija Djurisic

Nebojsa Bozanic

Papers citing "Extremely Simple Activation Shaping for Out-of-Distribution Detection"

7 / 7 papers shown

Title
Can We Detect Failures Without Failure Data? Uncertainty-Aware Runtime Failure Detection for Imitation Learning Policies Chen Xu Tony Nguyen Emma Dixon Christopher Rodriguez Patrick "Tree" Miller Robert Lee Paarth Shah Rares Ambrus Haruki Nishimura Masha Itkina OffRL 54 0 0 11 Mar 2025
Editing a classifier by rewriting its prediction rules Shibani Santurkar Dimitris Tsipras Mahalaxmi Elango David Bau Antonio Torralba A. Madry KELM 151 75 0 02 Dec 2021
Sparsity in Deep Learning: Pruning and growth for efficient inference and training in neural networks Torsten Hoefler Dan Alistarh Tal Ben-Nun Nikoli Dryden Alexandra Peste MQ 111 526 0 31 Jan 2021
Scaling Laws for Neural Language Models Jared Kaplan Sam McCandlish T. Henighan Tom B. Brown B. Chess R. Child Scott Gray Alec Radford Jeff Wu Dario Amodei 215 3,054 0 23 Jan 2020
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 253 4,940 0 05 Dec 2016
Densely Connected Convolutional Networks Gao Huang Zhuang Liu L. V. D. van der Maaten Kilian Q. Weinberger PINN 3DV 220 9,849 0 25 Aug 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 232 8,157 0 06 Jun 2015