Communities
Connect sessions
AI calendar
Organizations
Join Slack
Contact Sales
Search
Open menu
Home
Papers
All Papers
0 / 0 papers shown
Home
Papers
1907.08982
Cited By
v1
v2 (latest)
Noise Regularization for Conditional Density Estimation
21 July 2019
Jonas Rothfuss
Fabio Ferreira
S. Boehm
Simon Walther
Maxim Ulrich
Tamim Asfour
Andreas Krause
Re-assign community
ArXiv (abs)
PDF
HTML
Papers citing
"Noise Regularization for Conditional Density Estimation"
28 / 28 papers shown
Nonparametric estimation of conditional probability distributions using a generative approach based on conditional push-forward neural networks
Nicola Rares Franco
Lorenzo Tedesco
160
0
0
18 Nov 2025
Overlap-Adaptive Regularization for Conditional Average Treatment Effect Estimation
Valentyn Melnychuk
Dennis Frauen
Jonas Schweisthal
Stefan Feuerriegel
CML
127
0
0
29 Sep 2025
GDR-learners: Orthogonal Learning of Generative Models for Potential Outcomes
Valentyn Melnychuk
Stefan Feuerriegel
82
0
0
26 Sep 2025
Variational Autoencoder Framework for Hyperspectral Retrievals (Hyper-VAE) of Phytoplankton Absorption and Chlorophyll a in Coastal Waters for NASA's EMIT and PACE Missions
IEEE Transactions on Geoscience and Remote Sensing (IEEE TGRS), 2025
Jiadong Lou
Bingqing Liu
Yuanheng Xiong
Xiaodong Zhang
Xu Yuan
218
9
0
18 Apr 2025
CEC-MMR: Cross-Entropy Clustering Approach to Multi-Modal Regression
Krzysztof Byrski
Jacek Tabor
Przemysław Spurek
Marcin Mazur
142
0
0
09 Apr 2025
Quantifying Aleatoric Uncertainty of the Treatment Effect: A Novel Orthogonal Learner
Neural Information Processing Systems (NeurIPS), 2024
Valentyn Melnychuk
Stefan Feuerriegel
Mihaela van der Schaar
CML
491
5
0
05 Nov 2024
Conditional Density Estimation with Histogram Trees
Neural Information Processing Systems (NeurIPS), 2024
Lincen Yang
Matthijs van Leeuwen
184
2
0
15 Oct 2024
Flexible Conformal Highest Predictive Conditional Density Sets
Max Sampson
Kung-Sik Chan
282
2
0
26 Jun 2024
Predictability Analysis of Regression Problems via Conditional Entropy Estimations
Yu-Hsueh Fang
Chia-Yen Lee
104
1
0
06 Jun 2024
MGF: Mixed Gaussian Flow for Diverse Trajectory Prediction
Jiahe Chen
Jinkun Cao
Dahua Lin
Kris Kitani
Jiangmiao Pang
213
10
0
19 Feb 2024
Bounds on Representation-Induced Confounding Bias for Treatment Effect Estimation
Valentyn Melnychuk
Dennis Frauen
Stefan Feuerriegel
CML
311
19
0
19 Nov 2023
Partial Counterfactual Identification of Continuous Outcomes with a Curvature Sensitivity Model
Neural Information Processing Systems (NeurIPS), 2023
Valentyn Melnychuk
Dennis Frauen
Stefan Feuerriegel
513
13
0
02 Jun 2023
Anomaly Detection with Variance Stabilized Density Estimation
Conference on Uncertainty in Artificial Intelligence (UAI), 2023
Amit Rozner
Barak Battash
Henry Li
Lior Wolf
Ofir Lindenbaum
222
5
0
01 Jun 2023
IB-UQ: Information bottleneck based uncertainty quantification for neural function regression and neural operator learning
Journal of Computational Physics (JCP), 2023
Ling Guo
Hao Wu
Wenwen Zhou
Yan Wang
Tao Zhou
UQCV
312
21
0
07 Feb 2023
Normalizing Flows for Interventional Density Estimation
International Conference on Machine Learning (ICML), 2022
Valentyn Melnychuk
Dennis Frauen
Stefan Feuerriegel
418
24
0
13 Sep 2022
IL-flOw: Imitation Learning from Observation using Normalizing Flows
Wei-Di Chang
J. A. G. Higuera
Scott Fujimoto
David Meger
Gregory Dudek
121
10
0
19 May 2022
Short-Term Density Forecasting of Low-Voltage Load using Bernstein-Polynomial Normalizing Flows
IEEE Transactions on Smart Grid (IEEE Trans. Smart Grid), 2022
M. Arpogaus
Marcus Voss
Beate Sick
Mark Nigge-Uricher
Oliver Durr
199
20
0
29 Apr 2022
Multi-Asset Spot and Option Market Simulation
Magnus Wiese
Ben Wood
Alexandre Pachoud
R. Korn
Hans Buehler
Phillip Murray
Lianjun Bai
229
21
0
13 Dec 2021
Uncertainty estimation under model misspecification in neural network regression
Maria R. Cervera
Rafael Dätwyler
Francesco DÁngelo
Hamza Keurti
Benjamin Grewe
Christian Henning
186
6
0
23 Nov 2021
Contrastive Representation Learning with Trainable Augmentation Channel
Masanori Koyama
Kentaro Minami
Takeru Miyato
Y. Gal
156
1
0
15 Nov 2021
CLIP-Forge: Towards Zero-Shot Text-to-Shape Generation
Aditya Sanghi
Hang Chu
Joseph G. Lambourne
Ye Wang
Chin-Yi Cheng
Marco Fumero
Kamal Rahimi Malekshan
CLIP
365
342
0
06 Oct 2021
Meta-Learning Reliable Priors in the Function Space
Neural Information Processing Systems (NeurIPS), 2021
Jonas Rothfuss
Dominique Heyn
Jinfan Chen
Andreas Krause
260
29
0
06 Jun 2021
Deconvolutional Density Network: Modeling Free-Form Conditional Distributions
AAAI Conference on Artificial Intelligence (AAAI), 2021
Bing Chen
Mazharul Islam
Jisuo Gao
Lin Wang
BDL
CML
249
8
0
29 May 2021
RegFlow: Probabilistic Flow-based Regression for Future Prediction
Asian Conference on Intelligent Information and Database Systems (ACIIDS), 2020
Maciej Ziȩba
Marcin Przewiȩźlikowski
Marek Śmieja
Jacek Tabor
Tomasz Trzciñski
Przemysław Spurek
AI4TS
AI4CE
286
11
0
30 Nov 2020
Deep Conditional Transformation Models
Philipp F. M. Baumann
Torsten Hothorn
David Rügamer
325
30
0
15 Oct 2020
Why distillation helps: a statistical perspective
A. Menon
A. S. Rawat
Sashank J. Reddi
Seungyeon Kim
Sanjiv Kumar
FedML
232
25
0
21 May 2020
Deep transformation models: Tackling complex regression problems with neural network based transformation models
International Conference on Pattern Recognition (ICPR), 2020
Beate Sick
Torsten Hothorn
Oliver Durr
MedIm
BDL
OOD
UQCV
104
30
0
01 Apr 2020
PACOH: Bayes-Optimal Meta-Learning with PAC-Guarantees
International Conference on Machine Learning (ICML), 2020
Jonas Rothfuss
Vincent Fortuin
Martin Josifoski
Andreas Krause
UQCV
345
133
0
13 Feb 2020
1
