Neural Spline Flows

10 June 2019

Papers citing "Neural Spline Flows"

50 / 184 papers shown

Title
Conformal Contextual Robust Optimization Yash P. Patel Sahana Rayan Ambuj Tewari 42 17 0 16 Oct 2023
Discovering Mixtures of Structural Causal Models from Time Series Data Sumanth Varambally Yi Ma Rose Yu 22 5 0 10 Oct 2023
Stochastic interpolants with data-dependent couplings M. S. Albergo Mark Goldstein Nicholas M. Boffi Rajesh Ranganath Eric Vanden-Eijnden OT 37 30 0 05 Oct 2023
Doubly Robust Proximal Causal Learning for Continuous Treatments Yong Wu Yanwei Fu Shouyan Wang Xinwei Sun 26 1 0 22 Sep 2023
SE(3) Equivariant Augmented Coupling Flows Laurence I. Midgley Vincent Stimper Javier Antorán Emile Mathieu Bernhard Schölkopf José Miguel Hernández-Lobato 47 23 0 20 Aug 2023
A Review of Change of Variable Formulas for Generative Modeling Ullrich Kothe 34 6 0 04 Aug 2023
PC-Droid: Faster diffusion and improved quality for particle cloud generation Matthew Leigh Debasish Sengupta J. A. Raine Guillaume Quétant T. Golling DiffM 46 14 0 13 Jul 2023
A Heavy-Tailed Algebra for Probabilistic Programming Feynman T. Liang Liam Hodgkinson Michael W. Mahoney 23 3 0 15 Jun 2023
Partial Identifiability for Domain Adaptation Lingjing Kong Shaoan Xie Weiran Yao Yujia Zheng Guan-Hong Chen P. Stojanov Victor Akinwande Kun Zhang 53 9 0 10 Jun 2023
MESSY Estimation: Maximum-Entropy based Stochastic and Symbolic densitY Estimation Tony Tohme Mohsen Sadr K. Youcef-Toumi N. Hadjiconstantinou 30 3 0 07 Jun 2023
Nonparametric Identifiability of Causal Representations from Unknown Interventions Julius von Kügelgen M. Besserve Wendong Liang Luigi Gresele Armin Kekić Elias Bareinboim David M. Blei Bernhard Schölkopf CML 23 57 0 01 Jun 2023
Stochastic Pitch Prediction Improves the Diversity and Naturalness of Speech in Glow-TTS Sewade Ogun Vincent Colotte Emmanuel Vincent DiffM 35 4 0 28 May 2023
GC-Flow: A Graph-Based Flow Network for Effective Clustering Tianchun Wang F. Mirzazadeh Xinming Zhang Jing Chen BDL 50 7 0 26 May 2023
Bayesian calibration of differentiable agent-based models Arnau Quera-Bofarull Ayush Chopra Anisoara Calinescu Michael Wooldridge Joel Dyer 26 9 0 24 May 2023
Training Energy-Based Normalizing Flow with Score-Matching Objectives Chen-Hao Chao Wei-Fang Sun Yen-Chang Hsu Z. Kira Chun-Yi Lee 33 3 0 24 May 2023
Inductive Simulation of Calorimeter Showers with Normalizing Flows M. Buckley Claudius Krause Ian Pang David Shih AI4CE 24 22 0 19 May 2023
Computing high-dimensional optimal transport by flow neural networks Chen Xu Xiuyuan Cheng Yao Xie OT 45 4 0 19 May 2023
Machine Learning and the Future of Bayesian Computation Steven Winter Trevor Campbell Lizhen Lin Sanvesh Srivastava David B. Dunson TPM 47 4 0 21 Apr 2023
Semi-supervised Learning of Pushforwards For Domain Translation & Adaptation N. Panda Natalie Klein Dominic Yang P. Gasda Diane Oyen 32 1 0 18 Apr 2023
Continuous time recurrent neural networks: overview and application to forecasting blood glucose in the intensive care unit O. Fitzgerald O. Perez-Concha B. Gallego-Luxan Alejandro Metke-Jimenez Lachlan Rudd Louisa R Jorm BDL OOD AI4TS 36 0 0 14 Apr 2023
Neural Diffeomorphic Non-uniform B-spline Flows S. Hong S. Chun 40 1 0 07 Apr 2023
Ensemble weather forecast post-processing with a flexible probabilistic neural network approach P. Mlakar J. Merse Jana Faganeli Pucer 22 4 0 29 Mar 2023
Unsupervised Inference of Signed Distance Functions from Single Sparse Point Clouds without Learning Priors Chao Chen Yu-Shen Liu Zhizhong Han 3DPC 32 28 0 25 Mar 2023
Eryn : A multi-purpose sampler for Bayesian inference N. Karnesis Michael L. Katz N. Korsakova J. Gair N. Stergioulas 21 28 0 03 Mar 2023
Varianceflow: High-Quality and Controllable Text-to-Speech using Variance Information via Normalizing Flow Yoonhyung Lee Jinhyeok Yang Kyomin Jung 28 6 0 27 Feb 2023
Generative Invertible Quantum Neural Networks Armand Rousselot M. Spannowsky BDL 21 9 0 24 Feb 2023
Membership Inference Attacks against Synthetic Data through Overfitting Detection B. V. Breugel Hao Sun Zhaozhi Qian M. Schaar 33 45 0 24 Feb 2023
Comparative Study of Coupling and Autoregressive Flows through Robust Statistical Tests A. Coccaro Marco Letizia H. Reyes-González Riccardo Torre OOD 42 5 0 23 Feb 2023
Misspecification-robust Sequential Neural Likelihood for Simulation-based Inference Ryan P. Kelly David J. Nott David T. Frazier D. Warne Christopher C. Drovandi 35 10 0 31 Jan 2023
Neural Spline Search for Quantile Probabilistic Modeling Ruoxi Sun Chun-Liang Li Sercan Ö. Arik Michael W. Dusenberry Chen-Yu Lee Tomas Pfister AI4TS 42 5 0 12 Jan 2023
EPR-Net: Constructing non-equilibrium potential landscape via a variational force projection formulation Yue Zhao Wei Zhang Tiejun Li DiffM 21 8 0 05 Jan 2023
On the Robustness of Normalizing Flows for Inverse Problems in Imaging Seongmin Hong I. Park S. Chun 43 7 0 08 Dec 2022
Initial Results for Pairwise Causal Discovery Using Quantitative Information Flow Felipe Giori Flavio Figueiredo CML 22 1 0 02 Dec 2022
Accelerating Inverse Learning via Intelligent Localization with Exploratory Sampling Jiaxin Zhang Sirui Bi Victor Fung 35 3 0 02 Dec 2022
Denoising Deep Generative Models G. Loaiza-Ganem Brendan Leigh Ross Luhuan Wu John P. Cunningham Jesse C. Cresswell Anthony L. Caterini DiffM 36 5 0 30 Nov 2022
Proximal Residual Flows for Bayesian Inverse Problems J. Hertrich BDL TPM 41 4 0 30 Nov 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
Waveflow: Enforcing boundary conditions in smooth normalizing flows with application to fermionic wave functions Luca Thiede Chong Sun A. Aspuru‐Guzik 36 1 0 27 Nov 2022
CaloMan: Fast generation of calorimeter showers with density estimation on learned manifolds Jesse C. Cresswell Brendan Leigh Ross G. Loaiza-Ganem H. Reyes-González Marco Letizia Anthony L. Caterini 24 36 0 23 Nov 2022
Normalizing Flow with Variational Latent Representation Hanze Dong Shizhe Diao Weizhong Zhang Tong Zhang BDL OOD DRL 13 0 0 21 Nov 2022
Aspects of scaling and scalability for flow-based sampling of lattice QCD Ryan Abbott M. S. Albergo Aleksandar Botev D. Boyda Kyle Cranmer ... Ali Razavi Danilo Jimenez Rezende F. Romero-López P. Shanahan Julian M. Urban 32 33 0 14 Nov 2022
From Denoising Diffusions to Denoising Markov Models Joe Benton Yuyang Shi Valentin De Bortoli George Deligiannidis Arnaud Doucet DiffM 79 25 0 07 Nov 2022
Flows for Flows: Training Normalizing Flows Between Arbitrary Distributions with Maximum Likelihood Estimation Samuel Klein J. A. Raine T. Golling TPM 36 10 0 04 Nov 2022
Decorrelation with conditional normalizing flows Samuel Klein T. Golling 40 4 0 04 Nov 2022
ProbNeRF: Uncertainty-Aware Inference of 3D Shapes from 2D Images Matthew D. Hoffman T. Le Pavel Sountsov Christopher Suter Ben Lee Vikash K. Mansinghka Rif A. Saurous BDL 31 12 0 27 Oct 2022
Whitening Convergence Rate of Coupling-based Normalizing Flows Felix Dräxler Christoph Schnörr Ullrich Kothe 41 7 0 25 Oct 2022
Deformations of Boltzmann Distributions Bálint Máté Franccois Fleuret OT 28 2 0 25 Oct 2022
Are Deep Sequence Classifiers Good at Non-Trivial Generalization? Francesco Cazzaro A. Quattoni X. Carreras MQ 26 0 0 24 Oct 2022
Transport Reversible Jump Proposals L. Davies Roberto Salomone Matthew Sutton Christopher C. Drovandi BDL 27 1 0 22 Oct 2022
Sequential Neural Score Estimation: Likelihood-Free Inference with Conditional Score Based Diffusion Models Louis Sharrock J. Simons Song Liu Mark Beaumont DiffM 64 34 0 10 Oct 2022