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1302.0082
Cited By
Distribution-Free Distribution Regression
1 February 2013
Barnabás Póczós
Alessandro Rinaldo
Aarti Singh
Larry A. Wasserman
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Papers citing
"Distribution-Free Distribution Regression"
47 / 47 papers shown
Title
Bayesian Density-Density Regression with Application to Cell-Cell Communications
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Peter Mueller
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Improved learning theory for kernel distribution regression with two-stage sampling
François Bachoc
Louis Bethune
Alberto González Sanz
Jean-Michel Loubes
145
2
0
28 Jan 2025
Scalable Signature-Based Distribution Regression via Reference Sets
Andrew Alden
Carmine Ventre
Blanka Horvath
142
0
0
11 Oct 2024
Learning to Embed Distributions via Maximum Kernel Entropy
Oleksii Kachaiev
Stefano Recanatesi
OOD
120
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0
01 Aug 2024
Gaussian process regression with Sliced Wasserstein Weisfeiler-Lehman graph kernels
Raphael Carpintero Perez
Sébastien da Veiga
Josselin Garnier
B. Staber
107
6
0
06 Feb 2024
LearnedWMP: Workload Memory Prediction Using Distribution of Query Templates
Shaikh Quader
Andres Jaramillo
Sumona Mukhopadhyay
Ghadeer Abuoda
Calisto Zuzarte
David Kalmuk
Marin Litoiu
Manos Papagelis
33
1
0
22 Jan 2024
Learning Theory of Distribution Regression with Neural Networks
Zhongjie Shi
Zhan Yu
Ding-Xuan Zhou
32
2
0
07 Jul 2023
Statistical learning on measures: an application to persistence diagrams
Olympio Hacquard
Gilles Blanchard
Clément Levrard
134
3
0
15 Mar 2023
Direct Bayesian Regression for Distribution-valued Covariates
Bohao Tang
Sandipan Pramanik
Yi Zhao
B. Caffo
A. Datta
39
0
0
11 Mar 2023
Gaussian Processes on Distributions based on Regularized Optimal Transport
François Bachoc
Louis Bethune
Alberto González Sanz
Jean-Michel Loubes
GP
OT
66
8
0
12 Oct 2022
Coefficient-based Regularized Distribution Regression
Yuan Mao
Lei Shi
Zheng-Chu Guo
118
4
0
26 Aug 2022
Generalized Identifiability Bounds for Mixture Models with Grouped Samples
Robert A. Vandermeulen
René Saitenmacher
72
3
0
22 Jul 2022
Performance of Distribution Regression with Doubling Measure under the seek of Closest Point
Ilqar Ramazanli
52
3
0
01 Mar 2022
Distribution Regression with Sliced Wasserstein Kernels
Dimitri Meunier
Massimiliano Pontil
C. Ciliberto
OOD
72
17
0
08 Feb 2022
Label-Free Model Evaluation with Semi-Structured Dataset Representations
Xiaoxiao Sun
Yunzhong Hou
Hongdong Li
Liang Zheng
66
12
0
01 Dec 2021
A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification
Anastasios Nikolas Angelopoulos
Stephen Bates
OOD
271
625
0
15 Jul 2021
Robust Kernel-based Distribution Regression
Zhan Yu
D. Ho
Ding-Xuan Zhou
OOD
68
11
0
21 Apr 2021
Nonlinear Distribution Regression for Remote Sensing Applications
J. Adsuara
Adrián Pérez-Suay
Jordi Munoz-Marí
Anna Mateo-Sanchis
M. Piles
Gustau Camps-Valls
102
17
0
07 Dec 2020
Causal inference using deep neural networks
Ye Yuan
Xueying Ding
Z. Bar-Joseph
BDL
CML
50
2
0
25 Nov 2020
Stochastic Gradient Descent Meets Distribution Regression
Nicole Mücke
62
5
0
24 Oct 2020
Anomaly Detection at Scale: The Case for Deep Distributional Time Series Models
Fadhel Ayed
Lorenzo Stella
Tim Januschowski
Jan Gasthaus
AI4TS
103
10
0
30 Jul 2020
Estimates on Learning Rates for Multi-Penalty Distribution Regression
Zhan Yu
D. Ho
23
0
0
16 Jun 2020
Deep Kernels with Probabilistic Embeddings for Small-Data Learning
Ankur Mallick
Chaitanya Dwivedi
B. Kailkhura
Gauri Joshi
T. Y. Han
BDL
UQCV
44
8
0
13 Oct 2019
Dataset2Vec: Learning Dataset Meta-Features
H. Jomaa
Lars Schmidt-Thieme
Josif Grabocka
SSL
86
64
0
27 May 2019
3D Object Recognition with Ensemble Learning --- A Study of Point Cloud-Based Deep Learning Models
Daniel Koguciuk
L. Chechlinski
Tarek El-Gaaly
3DPC
48
11
0
17 Apr 2019
On Deep Set Learning and the Choice of Aggregations
Maximilian Sölch
A. Akhundov
Patrick van der Smagt
Justin Bayer
TDI
72
20
0
18 Mar 2019
Theoretical and Experimental Analysis on the Generalizability of Distribution Regression Network
C. Kou
H. Lee
Jorge Sanz
Teck Khim Ng
27
0
0
05 Nov 2018
Distribution regression model with a Reproducing Kernel Hilbert Space approach
T. T. T. Bui
Jean-Michel Loubes
Risser
Balaresque
58
11
0
27 Jun 2018
Causal effects based on distributional distances
Kwangho Kim
Jisu Kim
Edward H. Kennedy
CML
56
19
0
08 Jun 2018
A Compact Network Learning Model for Distribution Regression
C. Kou
H. Lee
Teck Khim Ng
64
10
0
13 Apr 2018
Kernel Embedding Approaches to Orbit Determination of Spacecraft Clusters
Srinagesh Sharma
J. Cutler
15
3
0
01 Mar 2018
Distance Measure Machines
A. Rakotomamonjy
Abraham Traoré
Maxime Bérar
Rémi Flamary
Nicolas Courty
64
12
0
01 Mar 2018
Estimating Cosmological Parameters from the Dark Matter Distribution
Siamak Ravanbakhsh
Junier Oliva
S. Fromenteau
Layne Price
S. Ho
J. Schneider
Barnabás Póczós
78
76
0
06 Nov 2017
Bayesian Approaches to Distribution Regression
H. Law
Danica J. Sutherland
Dino Sejdinovic
Seth Flaxman
OOD
UQCV
BDL
91
37
0
11 May 2017
Deep Sets
Manzil Zaheer
Satwik Kottur
Siamak Ravanbakhsh
Barnabás Póczós
Ruslan Salakhutdinov
Alex Smola
481
2,485
0
10 Mar 2017
A Gaussian Process Regression Model for Distribution Inputs
François Bachoc
Fabrice Gamboa
Jean-Michel Loubes
N. Venet
106
53
0
31 Jan 2017
Prototypal Analysis and Prototypal Regression
Chenyue Wu
E. Tabak
63
13
0
31 Jan 2017
From Dependence to Causation
David Lopez-Paz
OOD
CML
179
26
0
12 Jul 2016
Uncertain programming model for multi-item solid transportation problem
Hasan Dalman
155
64
0
31 May 2016
Operator-valued Kernels for Learning from Functional Response Data
Hachem Kadri
E. Duflos
Philippe Preux
S. Canu
A. Rakotomamonjy
Julien Audiffren
93
131
0
28 Oct 2015
Linear-time Learning on Distributions with Approximate Kernel Embeddings
Danica J. Sutherland
Junier B. Oliva
Barnabás Póczós
J. Schneider
61
18
0
24 Sep 2015
On The Identifiability of Mixture Models from Grouped Samples
Robert A. Vandermeulen
Clayton D. Scott
45
9
0
23 Feb 2015
Passing Expectation Propagation Messages with Kernel Methods
Wittawat Jitkrittum
Arthur Gretton
N. Heess
27
0
0
02 Jan 2015
Learning Theory for Distribution Regression
Z. Szabó
Bharath K. Sriperumbudur
Barnabás Póczós
Arthur Gretton
OOD
116
140
0
08 Nov 2014
Two-stage Sampled Learning Theory on Distributions
Z. Szabó
Arthur Gretton
Barnabás Póczós
Bharath K. Sriperumbudur
OOD
61
3
0
07 Feb 2014
Fast Distribution To Real Regression
Junier B. Oliva
Willie Neiswanger
Barnabás Póczós
J. Schneider
Eric Xing
91
45
0
10 Nov 2013
FuSSO: Functional Shrinkage and Selection Operator
Junier B. Oliva
Barnabás Póczós
Timothy D. Verstynen
Aarti Singh
J. Schneider
F. Yeh
W. Tseng
42
10
0
10 Nov 2013
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