Unconstrained Monotonic Neural Networks

14 August 2019

Papers citing "Unconstrained Monotonic Neural Networks"

34 / 34 papers shown

Title
Advancing Constrained Monotonic Neural Networks: Achieving Universal Approximation Beyond Bounded Activations Davide Sartor Alberto Sinigaglia Gian Antonio Susto 37 0 0 05 May 2025
Deep neural networks for choice analysis: Enhancing behavioral regularity with gradient regularization Siqi Feng Rui Yao Stephane Hess Ricardo A. Daziano Timothy Brathwaite Joan Walker Shenhao Wang 30 1 0 23 Apr 2024
TERM Model: Tensor Ring Mixture Model for Density Estimation Ruituo Wu Jiani Liu Ce Zhu Anh-Huy Phan Ivan Oseledets Yipeng Liu 31 1 0 13 Dec 2023
Incorporating LLM Priors into Tabular Learners Max Zhu Sinivsa Stanivuk Andrija Petrović Mladen Nikolic Pietro Lio 10 1 0 20 Nov 2023
Neural Bayes Estimators for Irregular Spatial Data using Graph Neural Networks Matthew Sainsbury-Dale A. Zammit‐Mangion J. Richards Raphael Huser 36 15 0 04 Oct 2023
Risk-Sensitive Policy with Distributional Reinforcement Learning Thibaut Théate D. Ernst OffRL 30 5 0 30 Dec 2022
Taming Hyperparameter Tuning in Continuous Normalizing Flows Using the JKO Scheme Alexander Vidal Samy Wu Fung Luis Tenorio Stanley Osher L. Nurbekyan 35 15 0 30 Nov 2022
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 Xuanxiang Huang Martin C. Cooper António Morgado Jordi Planes Sasha Rubin FAtt 38 18 0 27 Oct 2022
Whitening Convergence Rate of Coupling-based Normalizing Flows Felix Dräxler Christoph Schnörr Ullrich Kothe 41 7 0 25 Oct 2022
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 G. Morel Lucas Drumetz Simon Benaïchouche Nicolas Courty F. Rousseau OT 32 6 0 22 Sep 2022
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 Difeng Cai Yuliang Ji Huan He Qiang Ye Yuanzhe Xi TPM 33 4 0 05 Jun 2022
Invertible Neural Networks for Graph Prediction Chen Xu Xiuyuan Cheng Yao Xie GNN 31 9 0 02 Jun 2022
Efficient Reinforcement Learning from Demonstration Using Local Ensemble and Reparameterization with Split and Merge of Expert Policies Yu Wang Fang Liu 29 0 0 23 May 2022
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
Learning Temporal Point Processes for Efficient Retrieval of Continuous Time Event Sequences Vinayak Gupta Srikanta J. Bedathur A. De AI4TS 25 13 0 17 Feb 2022
Vehicle: Interfacing Neural Network Verifiers with Interactive Theorem Provers M. Daggitt Wen Kokke R. Atkey Luca Arnaboldi Ekaterina Komendantskaya 26 5 0 10 Feb 2022
Global Optimization Networks Sen Zhao Erez Louidor Ilan Oleksandr Mangylov Maya R. Gupta 29 5 0 02 Feb 2022
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
Multi-Asset Spot and Option Market Simulation Magnus Wiese Ben Wood Alexandre Pachoud R. Korn Hans Buehler Phillip Murray Lianjun Bai 27 21 0 13 Dec 2021
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 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 Sam Bond-Taylor Adam Leach Yang Long Chris G. Willcocks VLM TPM 41 483 0 08 Mar 2021
MALI: A memory efficient and reverse accurate integrator for Neural ODEs Juntang Zhuang Nicha Dvornek S. Tatikonda James S. Duncan 27 49 0 09 Feb 2021
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
Advances in the training, pruning and enforcement of shape constraints of Morphological Neural Networks using Tropical Algebra Nikolaos Dimitriadis Petros Maragos 19 9 0 15 Nov 2020
Neural Empirical Bayes: Source Distribution Estimation and its Applications to Simulation-Based Inference M. Vandegar Michael Kagan Antoine Wehenkel Gilles Louppe 29 27 0 11 Nov 2020
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 Aishwarya Sivaraman G. Farnadi T. Millstein Mathias Niepert 24 50 0 16 Jun 2020
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 Amir M. Rahimi Amirreza Shaban Ching-An Cheng Richard I. Hartley Byron Boots UQCV 14 68 0 15 Mar 2020
Normalizing Flows for Probabilistic Modeling and Inference George Papamakarios Eric T. Nalisnick Danilo Jimenez Rezende S. Mohamed Balaji Lakshminarayanan TPM AI4CE 62 1,631 0 05 Dec 2019