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Unconstrained Monotonic Neural Networks

Unconstrained Monotonic Neural Networks

14 August 2019
Antoine Wehenkel
Gilles Louppe
    TPM
ArXivPDFHTML

Papers citing "Unconstrained Monotonic Neural Networks"

28 / 28 papers shown
Title
Advancing Constrained Monotonic Neural Networks: Achieving Universal Approximation Beyond Bounded Activations
Advancing Constrained Monotonic Neural Networks: Achieving Universal Approximation Beyond Bounded Activations
Davide Sartor
Alberto Sinigaglia
Gian Antonio Susto
34
0
0
05 May 2025
TERM Model: Tensor Ring Mixture Model for Density Estimation
TERM Model: Tensor Ring Mixture Model for Density Estimation
Ruituo Wu
Jiani Liu
Ce Zhu
Anh-Huy Phan
Ivan Oseledets
Yipeng Liu
28
1
0
13 Dec 2023
Incorporating LLM Priors into Tabular Learners
Incorporating LLM Priors into Tabular Learners
Max Zhu
Sinivsa Stanivuk
Andrija Petrović
Mladen Nikolic
Pietro Lió
10
1
0
20 Nov 2023
Neural Bayes Estimators for Irregular Spatial Data using Graph Neural Networks
Neural Bayes Estimators for Irregular Spatial Data using Graph Neural Networks
Matthew Sainsbury-Dale
A. Zammit‐Mangion
J. Richards
Raphael Huser
28
15
0
04 Oct 2023
Risk-Sensitive Policy with Distributional Reinforcement Learning
Risk-Sensitive Policy with Distributional Reinforcement Learning
Thibaut Théate
D. Ernst
OffRL
30
5
0
30 Dec 2022
Learning to Optimize with Stochastic Dominance Constraints
Learning to Optimize with Stochastic Dominance Constraints
H. Dai
Yuan Xue
Niao He
B. Wang
Na Li
Dale Schuurmans
Bo Dai
22
6
0
14 Nov 2022
Feature Necessity & Relevancy in ML Classifier Explanations
Feature Necessity & Relevancy in ML Classifier Explanations
Xuanxiang Huang
Martin C. Cooper
António Morgado
Jordi Planes
Sasha Rubin
FAtt
32
18
0
27 Oct 2022
Whitening Convergence Rate of Coupling-based Normalizing Flows
Whitening Convergence Rate of Coupling-based Normalizing Flows
Felix Dräxler
Christoph Schnörr
Ullrich Kothe
36
7
0
25 Oct 2022
Neural Estimation of Submodular Functions with Applications to
  Differentiable Subset Selection
Neural Estimation of Submodular Functions with Applications to Differentiable Subset Selection
A. De
Soumen Chakrabarti
24
4
0
20 Oct 2022
Turning Normalizing Flows into Monge Maps with Geodesic Gaussian
  Preserving Flows
Turning Normalizing Flows into Monge Maps with Geodesic Gaussian Preserving Flows
G. Morel
Lucas Drumetz
Simon Benaïchouche
Nicolas Courty
F. Rousseau
OT
30
6
0
22 Sep 2022
CheckINN: Wide Range Neural Network Verification in Imandra (Extended)
CheckINN: Wide Range Neural Network Verification in Imandra (Extended)
Remi Desmartin
Grant Passmore
Ekaterina Komendantskaya
M. Daggitt
26
5
0
21 Jul 2022
AUTM Flow: Atomic Unrestricted Time Machine for Monotonic Normalizing
  Flows
AUTM Flow: Atomic Unrestricted Time Machine for Monotonic Normalizing Flows
Difeng Cai
Yuliang Ji
Huan He
Q. Ye
Yuanzhe Xi
TPM
30
4
0
05 Jun 2022
Invertible Neural Networks for Graph Prediction
Invertible Neural Networks for Graph Prediction
Chen Xu
Xiuyuan Cheng
Yao Xie
GNN
28
9
0
02 Jun 2022
Efficient Reinforcement Learning from Demonstration Using Local Ensemble
  and Reparameterization with Split and Merge of Expert Policies
Efficient Reinforcement Learning from Demonstration Using Local Ensemble and Reparameterization with Split and Merge of Expert Policies
Yu Wang
Fang Liu
21
0
0
23 May 2022
TO-FLOW: Efficient Continuous Normalizing Flows with Temporal
  Optimization adjoint with Moving Speed
TO-FLOW: Efficient Continuous Normalizing Flows with Temporal Optimization adjoint with Moving Speed
Shian Du
Yihong Luo
Wei Chen
Jian Xu
Delu Zeng
32
7
0
19 Mar 2022
Vehicle: Interfacing Neural Network Verifiers with Interactive Theorem
  Provers
Vehicle: Interfacing Neural Network Verifiers with Interactive Theorem Provers
M. Daggitt
Wen Kokke
R. Atkey
Luca Arnaboldi
Ekaterina Komendantskaya
23
5
0
10 Feb 2022
Global Optimization Networks
Global Optimization Networks
Sen Zhao
Erez Louidor Ilan
Oleksandr Mangylov
Maya R. Gupta
26
5
0
02 Feb 2022
Triangular Flows for Generative Modeling: Statistical Consistency,
  Smoothness Classes, and Fast Rates
Triangular Flows for Generative Modeling: Statistical Consistency, Smoothness Classes, and Fast Rates
N. J. Irons
M. Scetbon
Soumik Pal
Zaïd Harchaoui
33
17
0
31 Dec 2021
Sparse Flows: Pruning Continuous-depth Models
Sparse Flows: Pruning Continuous-depth Models
Lucas Liebenwein
Ramin Hasani
Alexander Amini
Daniela Rus
26
16
0
24 Jun 2021
A deep generative model for probabilistic energy forecasting in power
  systems: normalizing flows
A deep generative model for probabilistic energy forecasting in power systems: normalizing flows
Jonathan Dumas
Antoine Wehenkel
Bertrand Cornélusse
Antonio Sutera
AI4TS
32
82
0
17 Jun 2021
Deep Generative Modelling: A Comparative Review of VAEs, GANs,
  Normalizing Flows, Energy-Based and Autoregressive Models
Deep Generative Modelling: A Comparative Review of VAEs, GANs, Normalizing Flows, Energy-Based and Autoregressive Models
Sam Bond-Taylor
Adam Leach
Yang Long
Chris G. Willcocks
VLM
TPM
41
481
0
08 Mar 2021
MALI: A memory efficient and reverse accurate integrator for Neural ODEs
MALI: A memory efficient and reverse accurate integrator for Neural ODEs
Juntang Zhuang
Nicha Dvornek
S. Tatikonda
James S. Duncan
24
49
0
09 Feb 2021
Convex Potential Flows: Universal Probability Distributions with Optimal
  Transport and Convex Optimization
Convex Potential Flows: Universal Probability Distributions with Optimal Transport and Convex Optimization
Chin-Wei Huang
Ricky T. Q. Chen
Christos Tsirigotis
Aaron Courville
OT
119
95
0
10 Dec 2020
Neural Empirical Bayes: Source Distribution Estimation and its
  Applications to Simulation-Based Inference
Neural Empirical Bayes: Source Distribution Estimation and its Applications to Simulation-Based Inference
M. Vandegar
Michael Kagan
Antoine Wehenkel
Gilles Louppe
24
27
0
11 Nov 2020
Variational Disentanglement for Rare Event Modeling
Variational Disentanglement for Rare Event Modeling
Zidi Xiu
Chenyang Tao
M. Gao
Connor Davis
B. Goldstein
Ricardo Henao
CML
DRL
32
6
0
17 Sep 2020
Counterexample-Guided Learning of Monotonic Neural Networks
Counterexample-Guided Learning of Monotonic Neural Networks
Aishwarya Sivaraman
G. Farnadi
T. Millstein
Mathias Niepert
24
50
0
16 Jun 2020
Consistent and Flexible Selectivity Estimation for High-Dimensional Data
Consistent and Flexible Selectivity Estimation for High-Dimensional Data
Yaoshu Wang
Chuan Xiao
Jianbin Qin
Rui Mao
Onizuka Makoto
Wei Wang
Rui Zhang
Yoshiharu Ishikawa
33
14
0
20 May 2020
Intra Order-preserving Functions for Calibration of Multi-Class Neural
  Networks
Intra Order-preserving Functions for Calibration of Multi-Class Neural Networks
Amir M. Rahimi
Amirreza Shaban
Ching-An Cheng
Richard I. Hartley
Byron Boots
UQCV
14
68
0
15 Mar 2020
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