v1v2 (latest)

Neural SDEs as Infinite-Dimensional GANs

6 February 2021

Papers citing "Neural SDEs as Infinite-Dimensional GANs"

49 / 49 papers shown

Title
Towards Identifiability of Interventional Stochastic Differential Equations Aaron Zweig Zaikang Lin Elham Azizi David A. Knowles 59 1 0 21 May 2025
Filtered not Mixed: Stochastic Filtering-Based Online Gating for Mixture of Large Language Models Raeid Saqur Anastasis Kratsios Florian Krach Yannick Limmer Jacob-Junqi Tian John Willes Blanka Horvath Frank Rudzicz MoE 130 0 0 24 Feb 2025
Graph Pseudotime Analysis and Neural Stochastic Differential Equations for Analyzing Retinal Degeneration Dynamics and Beyond Dai Shi Kuan Yan Lequan Lin Yue Zeng Ting Zhang D. Matsypura Mark C. Gillies Ling Zhu Junbin Gao 162 1 0 10 Feb 2025
Trajectory Flow Matching with Applications to Clinical Time Series Modeling Xi Zhang Yuan Pu Yuki Kawamura Andrew Loza Yoshua Bengio Dennis L. Shung Alexander Tong OOD AI4TS MedIm 91 9 0 28 Oct 2024
Efficient, Accurate and Stable Gradients for Neural ODEs Sam McCallum James Foster 77 6 0 15 Oct 2024
Efficient Training of Neural Stochastic Differential Equations by Matching Finite Dimensional Distributions Jianxin Zhang Josh Viktorov Doosan Jung Emily Pitler DiffM 203 0 0 04 Oct 2024
Closed-Loop Long-Horizon Robotic Planning via Equilibrium Sequence Modeling Jinghan Li Zhicheng Sun Fei Li 162 2 0 02 Oct 2024
Neural Differential Appearance Equations Chen Liu Tobias Ritschel 83 0 0 23 Sep 2024
MD-NOMAD: Mixture density nonlinear manifold decoder for emulating stochastic differential equations and uncertainty propagation Akshay Thakur Souvik Chakraborty 59 1 0 24 Apr 2024
Generative Adversarial Networks Gilad Cohen Raja Giryes GAN 283 30,149 0 01 Mar 2022
Score-Based Generative Modeling through Stochastic Differential Equations Yang Song Jascha Narain Sohl-Dickstein Diederik P. Kingma Abhishek Kumar Stefano Ermon Ben Poole DiffM SyDa 350 6,551 0 26 Nov 2020
Robust pricing and hedging via neural SDEs Patryk Gierjatowicz Marc Sabate Vidales David Siska Lukasz Szpruch Zan Zuric 69 34 0 08 Jul 2020
Denoising Diffusion Probabilistic Models Jonathan Ho Ajay Jain Pieter Abbeel DiffM 669 18,276 0 19 Jun 2020
Multiscale Deep Equilibrium Models Shaojie Bai V. Koltun J. Zico Kolter BDL 89 211 0 15 Jun 2020
On Second Order Behaviour in Augmented Neural ODEs Alexander Norcliffe Cristian Bodnar Ben Day Nikola Simidjievski Pietro Lio 70 94 0 12 Jun 2020
Neural Controlled Differential Equations for Irregular Time Series Patrick Kidger James Morrill James Foster Terry Lyons AI4TS 111 481 0 18 May 2020
A generative adversarial network approach to calibration of local stochastic volatility models Christa Cuchiero Wahid Khosrawi Josef Teichmann GAN 152 69 0 05 May 2020
Lagrangian Neural Networks M. Cranmer S. Greydanus Stephan Hoyer Peter W. Battaglia D. Spergel S. Ho PINN 173 437 0 10 Mar 2020
Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows Ruizhi Deng B. Chang Marcus A. Brubaker Greg Mori Andreas M. Lehrmann 54 50 0 24 Feb 2020
Stochasticity in Neural ODEs: An Empirical Study V. Oganesyan Alexandra Volokhova Dmitry Vetrov BDL 68 20 0 22 Feb 2020
Dissecting Neural ODEs Stefano Massaroli Michael Poli Jinkyoo Park Atsushi Yamashita Hajime Asama 99 204 0 19 Feb 2020
Stochastic Normalizing Flows Hao Wu Jonas Köhler Frank Noé 131 185 0 16 Feb 2020
Universal Differential Equations for Scientific Machine Learning Christopher Rackauckas Yingbo Ma Julius Martensen Collin Warner K. Zubov R. Supekar Dominic J. Skinner Ali Ramadhan Alan Edelman AI4CE 88 597 0 13 Jan 2020
Signatory: differentiable computations of the signature and logsignature transforms, on both CPU and GPU Patrick Kidger Terry Lyons 76 84 0 03 Jan 2020
PyTorch: An Imperative Style, High-Performance Deep Learning Library Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury ... Sasank Chilamkurthy Benoit Steiner Lu Fang Junjie Bai Soumith Chintala ODL 523 42,559 0 03 Dec 2019
Deep Equilibrium Models Shaojie Bai J. Zico Kolter V. Koltun 94 671 0 03 Sep 2019
A Differentiable Programming System to Bridge Machine Learning and Scientific Computing Mike Innes Alan Edelman Keno Fischer Chris Rackauckas Elliot Saba Viral B. Shah Will Tebbutt PINN 53 184 0 17 Jul 2019
Generative Modeling by Estimating Gradients of the Data Distribution Yang Song Stefano Ermon SyDa DiffM 258 3,954 0 12 Jul 2019
Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances Csaba Tóth Harald Oberhauser 36 9 0 19 Jun 2019
Statistical Inference for Generative Models with Maximum Mean Discrepancy François‐Xavier Briol Alessandro Barp Andrew B. Duncan Mark Girolami 53 72 0 13 Jun 2019
Neural SDE: Stabilizing Neural ODE Networks with Stochastic Noise Xuanqing Liu Tesi Xiao Si Si Qin Cao Sanjiv Kumar Cho-Jui Hsieh 78 138 0 05 Jun 2019
Neural Stochastic Differential Equations: Deep Latent Gaussian Models in the Diffusion Limit Belinda Tzen Maxim Raginsky DiffM 166 210 0 23 May 2019
Universal Approximation with Deep Narrow Networks Patrick Kidger Terry Lyons 130 333 0 21 May 2019
Theoretical guarantees for sampling and inference in generative models with latent diffusions Belinda Tzen Maxim Raginsky DiffM 64 101 0 05 Mar 2019
FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models Will Grathwohl Ricky T. Q. Chen J. Bettencourt Ilya Sutskever David Duvenaud DRL 154 881 0 02 Oct 2018
Neural Ordinary Differential Equations T. Chen Yulia Rubanova J. Bettencourt David Duvenaud AI4CE 417 5,156 0 19 Jun 2018
The Unusual Effectiveness of Averaging in GAN Training Yasin Yazici Chuan-Sheng Foo Stefan Winkler Kim-Hui Yap Georgios Piliouras V. Chandrasekhar 113 174 0 12 Jun 2018
Spectral Normalization for Generative Adversarial Networks Takeru Miyato Toshiki Kataoka Masanori Koyama Yuichi Yoshida ODL 159 4,442 0 16 Feb 2018
Demystifying MMD GANs Mikolaj Binkowski Danica J. Sutherland Michael Arbel Arthur Gretton EGVM 157 1,500 0 04 Jan 2018
Learning to Detect Sepsis with a Multitask Gaussian Process RNN Classifier Joseph D. Futoma S. Hariharan Katherine A. Heller 58 173 0 13 Jun 2017
Real-valued (Medical) Time Series Generation with Recurrent Conditional GANs Cristóbal Esteban Stephanie L. Hyland Gunnar Rätsch GAN SyDa MedIm 112 791 0 08 Jun 2017
MMD GAN: Towards Deeper Understanding of Moment Matching Network Chun-Liang Li Wei-Cheng Chang Yu Cheng Yiming Yang Barnabás Póczós GAN 66 724 0 24 May 2017
Improved Training of Wasserstein GANs Ishaan Gulrajani Faruk Ahmed Martín Arjovsky Vincent Dumoulin Aaron Courville GAN 227 9,558 0 31 Mar 2017
A scalable end-to-end Gaussian process adapter for irregularly sampled time series classification Steven Cheng-Xian Li Benjamin M. Marlin AI4TS BDL 52 87 0 14 Jun 2016
Kernels for sequentially ordered data Franz J. Király Harald Oberhauser 381 135 0 29 Jan 2016
Variational Inference with Normalizing Flows Danilo Jimenez Rezende S. Mohamed DRL BDL 318 4,197 0 21 May 2015
Generative Moment Matching Networks Yujia Li Kevin Swersky R. Zemel OOD GAN 110 847 0 10 Feb 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 2.0K 150,260 0 22 Dec 2014
ADADELTA: An Adaptive Learning Rate Method Matthew D. Zeiler ODL 161 6,630 0 22 Dec 2012