Efficient and Accurate Gradients for Neural SDEs

27 May 2021

Papers citing "Efficient and Accurate Gradients for Neural SDEs"

49 / 49 papers shown

Title
Efficient Training of Neural SDEs Using Stochastic Optimal Control Rembert Daems Manfred Opper Guillaume Crevecoeur Tolga Birdal 38 0 0 22 May 2025
A Reversible Solver for Diffusion SDEs Zander W. Blasingame Chen Liu DiffM 85 0 0 12 Feb 2025
From discrete-time policies to continuous-time diffusion samplers: Asymptotic equivalences and faster training Julius Berner Lorenz Richter Marcin Sendera Jarrid Rector-Brooks Nikolay Malkin OffRL 95 8 0 10 Jan 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 70 7 0 28 Oct 2024
Efficient, Accurate and Stable Gradients for Neural ODEs Sam McCallum James Foster 70 5 0 15 Oct 2024
AdjointDEIS: Efficient Gradients for Diffusion Models Zander W. Blasingame Chen Liu DiffM 77 5 0 23 May 2024
Scaling ResNets in the Large-depth Regime Pierre Marion Adeline Fermanian Gérard Biau Jean-Philippe Vert 61 16 0 14 Jun 2022
SigGPDE: Scaling Sparse Gaussian Processes on Sequential Data M. Lemercier C. Salvi Thomas Cass Edwin V. Bonilla Theodoros Damoulas Terry Lyons 47 25 0 10 May 2021
Neural ODE Processes Alexander Norcliffe Cristian Bodnar Ben Day Jacob Moss Pietro Lio BDL AI4TS 58 64 0 23 Mar 2021
Momentum Residual Neural Networks Michael E. Sander Pierre Ablin Mathieu Blondel Gabriel Peyré 53 58 0 15 Feb 2021
Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations Winnie Xu Ricky T. Q. Chen Xuechen Li David Duvenaud BDL UQCV 52 48 0 12 Feb 2021
MALI: A memory efficient and reverse accurate integrator for Neural ODEs Juntang Zhuang Nicha Dvornek S. Tatikonda James S. Duncan 57 52 0 09 Feb 2021
Neural SDEs as Infinite-Dimensional GANs Patrick Kidger James Foster Xuechen Li Harald Oberhauser Terry Lyons DiffM 32 150 0 06 Feb 2021
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 294 6,409 0 26 Nov 2020
Neural Rough Differential Equations for Long Time Series James Morrill C. Salvi Patrick Kidger James Foster Terry Lyons AI4TS 66 132 0 17 Sep 2020
SDE-Net: Equipping Deep Neural Networks with Uncertainty Estimates Lingkai Kong Jimeng Sun Chao Zhang UQCV 86 106 0 24 Aug 2020
Robust pricing and hedging via neural SDEs Patryk Gierjatowicz Marc Sabate Vidales David Siska Lukasz Szpruch Zan Zuric 54 34 0 08 Jul 2020
The Signature Kernel is the solution of a Goursat PDE C. Salvi Thomas Cass James Foster Terry Lyons Weixin Yang SyDa 324 57 0 26 Jun 2020
Neural Jump Ordinary Differential Equations: Consistent Continuous-Time Prediction and Filtering Calypso Herrera Florian Krach Josef Teichmann BDL AI4TS 35 32 0 08 Jun 2020
Neural Controlled Differential Equations for Irregular Time Series Patrick Kidger James Morrill James Foster Terry Lyons AI4TS 90 470 0 18 May 2020
Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows Ruizhi Deng B. Chang Marcus A. Brubaker Greg Mori Andreas M. Lehrmann 42 50 0 24 Feb 2020
Stochastic Normalizing Flows Hao Wu Jonas Köhler Frank Noé 110 184 0 16 Feb 2020
Signatory: differentiable computations of the signature and logsignature transforms, on both CPU and GPU Patrick Kidger Terry Lyons 61 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 386 42,299 0 03 Dec 2019
Analyzing and Improving the Image Quality of StyleGAN Tero Karras S. Laine M. Aittala Janne Hellsten J. Lehtinen Timo Aila GAN 260 5,797 0 03 Dec 2019
Residual Flows for Invertible Generative Modeling Ricky T. Q. Chen Jens Behrmann David Duvenaud J. Jacobsen BDL TPM DRL 94 377 0 06 Jun 2019
Neural SDE: Stabilizing Neural ODE Networks with Stochastic Noise Xuanqing Liu Tesi Xiao Si Si Qin Cao Sanjiv Kumar Cho-Jui Hsieh 67 136 0 05 Jun 2019
GRU-ODE-Bayes: Continuous modeling of sporadically-observed time series E. Brouwer Jaak Simm Adam Arany Yves Moreau SyDa CML AI4TS 91 295 0 29 May 2019
ODE $^2$ VAE: Deep generative second order ODEs with Bayesian neural networks Çağatay Yıldız Markus Heinonen Harri Lähdesmäki BDL DRL 61 88 0 27 May 2019
Neural Jump Stochastic Differential Equations Junteng Jia Austin R. Benson BDL 57 225 0 24 May 2019
Neural Stochastic Differential Equations: Deep Latent Gaussian Models in the Diffusion Limit Belinda Tzen Maxim Raginsky DiffM 154 209 0 23 May 2019
Universal Approximation with Deep Narrow Networks Patrick Kidger Terry Lyons 111 330 0 21 May 2019
Deep Signature Transforms Patrick Kidger Patrick Kidger Imanol Perez Arribas C. Salvi Terry Lyons SLR 134 130 0 21 May 2019
Theoretical guarantees for sampling and inference in generative models with latent diffusions Belinda Tzen Maxim Raginsky DiffM 59 101 0 05 Mar 2019
AntisymmetricRNN: A Dynamical System View on Recurrent Neural Networks B. Chang Minmin Chen E. Haber Ed H. Chi PINN GNN 98 204 0 26 Feb 2019
Invertible Residual Networks Jens Behrmann Will Grathwohl Ricky T. Q. Chen David Duvenaud J. Jacobsen UQCV TPM 110 622 0 02 Nov 2018
Neural Ordinary Differential Equations T. Chen Yulia Rubanova J. Bettencourt David Duvenaud AI4CE 363 5,081 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 104 175 0 12 Jun 2018
Averaging Weights Leads to Wider Optima and Better Generalization Pavel Izmailov Dmitrii Podoprikhin T. Garipov Dmitry Vetrov A. Wilson FedML MoMe 112 1,658 0 14 Mar 2018
Spectral Normalization for Generative Adversarial Networks Takeru Miyato Toshiki Kataoka Masanori Koyama Yuichi Yoshida ODL 155 4,433 0 16 Feb 2018
Searching for Activation Functions Prajit Ramachandran Barret Zoph Quoc V. Le 62 606 0 16 Oct 2017
MMD GAN: Towards Deeper Understanding of Moment Matching Network Chun-Liang Li Wei-Cheng Chang Yu Cheng Yiming Yang Barnabás Póczós GAN 66 721 0 24 May 2017
Improved Training of Wasserstein GANs Ishaan Gulrajani Faruk Ahmed Martín Arjovsky Vincent Dumoulin Aaron Courville GAN 181 9,533 0 31 Mar 2017
Sigmoid-Weighted Linear Units for Neural Network Function Approximation in Reinforcement Learning Stefan Elfwing E. Uchibe Kenji Doya 122 1,717 0 10 Feb 2017
Gaussian Error Linear Units (GELUs) Dan Hendrycks Kevin Gimpel 165 4,994 0 27 Jun 2016
Kernels for sequentially ordered data Franz J. Király Harald Oberhauser 342 135 0 29 Jan 2016
Generative Moment Matching Networks Yujia Li Kevin Swersky R. Zemel OOD GAN 98 846 0 10 Feb 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.5K 149,842 0 22 Dec 2014
ADADELTA: An Adaptive Learning Rate Method Matthew D. Zeiler ODL 132 6,623 0 22 Dec 2012