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Towards a theory of out-of-distribution learning

Towards a theory of out-of-distribution learning

29 September 2021
Jayanta Dey
Ali Geisa
Ronak D. Mehta
Tyler M. Tomita
Hayden S. Helm
Haoyin Xu
Eric Eaton
Jeffery Dick
Carey E. Priebe
Joshua T. Vogelstein
    OOD
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Papers citing "Towards a theory of out-of-distribution learning"

11 / 11 papers shown
Title
Disentangled Representations for Causal Cognition
Disentangled Representations for Causal Cognition
Filippo Torresan
Manuel Baltieri
CML
27
1
0
30 Jun 2024
Tracking the perspectives of interacting language models
Tracking the perspectives of interacting language models
Hayden Helm
Brandon Duderstadt
Youngser Park
Carey E. Priebe
33
6
0
17 Jun 2024
Statistical Context Detection for Deep Lifelong Reinforcement Learning
Statistical Context Detection for Deep Lifelong Reinforcement Learning
Jeffery Dick
Saptarshi Nath
Christos Peridis
Eseoghene Ben-Iwhiwhu
Soheil Kolouri
Andrea Soltoggio
OffRL
48
0
0
29 May 2024
Deep and shallow data science for multi-scale optical neuroscience
Deep and shallow data science for multi-scale optical neuroscience
Gal Mishne
Adam Charles
13
1
0
13 Feb 2024
A Domain-Agnostic Approach for Characterization of Lifelong Learning
  Systems
A Domain-Agnostic Approach for Characterization of Lifelong Learning Systems
Megan M. Baker
Alexander New
Mario Aguilar-Simon
Ziad Al-Halah
Sébastien M. R. Arnold
...
Zifan Xu
A. Yanguas-Gil
Harel Yedidsion
Shangqun Yu
Gautam K. Vallabha
15
15
0
18 Jan 2023
Dimensionless machine learning: Imposing exact units equivariance
Dimensionless machine learning: Imposing exact units equivariance
Soledad Villar
Weichi Yao
D. Hogg
Ben Blum-Smith
Bianca Dumitrascu
9
26
0
02 Apr 2022
Mental State Classification Using Multi-graph Features
Mental State Classification Using Multi-graph Features
Guodong Chen
Hayden S. Helm
Kate Lytvynets
Weiwei Yang
Carey E. Priebe
14
8
0
25 Feb 2022
Prospective Learning: Principled Extrapolation to the Future
Prospective Learning: Principled Extrapolation to the Future
Ashwin De Silva
Rahul Ramesh
Pallavi V. Kulkarni
M. Shuler
Noah J. Cowan
...
Andrei A. Rusu
Timothy D. Verstynen
Konrad Paul Kording
Pratik Chaudhari
Joshua T. Vogelstein
AI4TS
21
2
0
19 Jan 2022
A benchmark with decomposed distribution shifts for 360 monocular depth
  estimation
A benchmark with decomposed distribution shifts for 360 monocular depth estimation
G. Albanis
N. Zioulis
Petros Drakoulis
Federico Álvarez
D. Zarpalas
P. Daras
MDE
20
0
0
01 Dec 2021
Simplest Streaming Trees
Simplest Streaming Trees
Haoyin Xu
Jayanta Dey
Sambit Panda
Joshua T. Vogelstein
6
0
0
16 Oct 2021
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Chelsea Finn
Pieter Abbeel
Sergey Levine
OOD
243
11,568
0
09 Mar 2017
1