ResearchTrend.AI
  • Communities
  • Connect sessions
  • AI calendar
  • Organizations
  • Join Slack
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2026 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2102.03657
  4. Cited By
Neural SDEs as Infinite-Dimensional GANs
v1v2 (latest)

Neural SDEs as Infinite-Dimensional GANs

International Conference on Machine Learning (ICML), 2021
6 February 2021
Patrick Kidger
James Foster
Xuechen Li
Harald Oberhauser
Terry Lyons
    DiffM
ArXiv (abs)PDFHTML

Papers citing "Neural SDEs as Infinite-Dimensional GANs"

50 / 117 papers shown
Scalable learning of macroscopic stochastic dynamics
Scalable learning of macroscopic stochastic dynamics
Mengyi Chen
Pengru Huang
K. Novoselov
Qianxiao Li
AI4CE
145
0
0
17 Nov 2025
RNAGenScape: Property-guided Optimization and Interpolation of mRNA Sequences with Manifold Langevin Dynamics
RNAGenScape: Property-guided Optimization and Interpolation of mRNA Sequences with Manifold Langevin Dynamics
Danqi Liao
Chen Liu
Xingzhi Sun
Dié Tang
Haochen Wang
...
Srikar Krishna Gopinath
Haejeong Lee
Ethan C. Strayer
Antonio J. Giraldez
Smita Krishnaswamy
123
0
0
14 Oct 2025
Deep Neural Networks Inspired by Differential Equations
Deep Neural Networks Inspired by Differential Equations
Y. Liu
Lianfang Wang
Kuilin Qin
Qinghua Zhang
Faqiang Wang
Li-min Cui
Jun Liu
Yuping Duan
T. Zeng
AI4TSAI4CE
207
0
0
09 Oct 2025
Reversible Deep Equilibrium Models
Reversible Deep Equilibrium Models
Sam McCallum
Kamran Arora
James Foster
216
3
0
16 Sep 2025
Flow Straight and Fast in Hilbert Space: Functional Rectified Flow
Flow Straight and Fast in Hilbert Space: Functional Rectified Flow
Jianxin Zhang
Clayton Scott
142
1
0
12 Sep 2025
Learning Generalized Hamiltonian Dynamics with Stability from Noisy Trajectory Data
Learning Generalized Hamiltonian Dynamics with Stability from Noisy Trajectory Data
Luke McLennan
Yi Wang
Ryan Farell
Minh Nguyen
Chandrajit Bajaj
97
0
0
08 Sep 2025
Beyond Ensembles: Simulating All-Atom Protein Dynamics in a Learned Latent Space
Beyond Ensembles: Simulating All-Atom Protein Dynamics in a Learned Latent Space
Aditya Sengar
Ali Hariri
P. Vandergheynst
Patrick Barth
AI4CE
306
0
0
02 Sep 2025
Modeling Irregular Astronomical Time Series with Neural Stochastic Delay Differential Equations
Modeling Irregular Astronomical Time Series with Neural Stochastic Delay Differential Equations
YongKyung Oh
Seungsu Kam
Dong-Young Lim
Sungil Kim
AI4TS
99
0
0
24 Aug 2025
Sig-DEG for Distillation: Making Diffusion Models Faster and Lighter
Sig-DEG for Distillation: Making Diffusion Models Faster and Lighter
Lei Jiang
Wen Ge
Niels Cariou-Kotlarek
Mingxuan Yi
Po-yu Chen
Lingyi Yang
Francois Buet-Golfouse
Gaurav Mittal
Hao Ni
DiffM
196
0
0
23 Aug 2025
Neural Stochastic Differential Equations on Compact State-Spaces
Neural Stochastic Differential Equations on Compact State-Spaces
Yue-Jane Liu
Malinda Lu
Matthew K. Nock
Yaniv Yacoby
139
0
0
23 Aug 2025
Multi-Marginal Stochastic Flow Matching for High-Dimensional Snapshot Data at Irregular Time Points
Multi-Marginal Stochastic Flow Matching for High-Dimensional Snapshot Data at Irregular Time Points
Justin Lee
Behnaz Moradijamei
Heman Shakeri
112
6
0
06 Aug 2025
CTBench: Cryptocurrency Time Series Generation Benchmark
CTBench: Cryptocurrency Time Series Generation Benchmark
Yihao Ang
Qiang Wang
Qiang Huang
Yifan Bao
Xinyu Xi
A. Tung
Chen Jin
Zhiyong Huang
AI4TS
134
2
0
03 Aug 2025
Fourier Neural Operators for Non-Markovian Processes:Approximation Theorems and Experiments
Fourier Neural Operators for Non-Markovian Processes:Approximation Theorems and Experiments
Wonjae Lee
Taeyoung Kim
Hyungbin Park
150
1
0
23 Jul 2025
Stable CDE Autoencoders with Acuity Regularization for Offline Reinforcement Learning in Sepsis Treatment
Stable CDE Autoencoders with Acuity Regularization for Offline Reinforcement Learning in Sepsis Treatment
Yue Gao
OffRLOODAI4TS
175
0
0
17 Jun 2025
Anomaly Detection and Generation with Diffusion Models: A Survey
Anomaly Detection and Generation with Diffusion Models: A Survey
Zehua Wang
Jing Liu
Chengfang Li
Rui Xi
W. Li
Liang Cao
Jin Wang
L. Yang
Junsong Yuan
Wei Zhou
DiffMMedIm
245
6
0
11 Jun 2025
Sample-Specific Noise Injection For Diffusion-Based Adversarial Purification
Sample-Specific Noise Injection For Diffusion-Based Adversarial Purification
Yuhao Sun
Jiacheng Zhang
Zesheng Ye
Chaowei Xiao
Feng Liu
DiffM
228
2
0
06 Jun 2025
HD-NDEs: Neural Differential Equations for Hallucination Detection in LLMs
HD-NDEs: Neural Differential Equations for Hallucination Detection in LLMsAnnual Meeting of the Association for Computational Linguistics (ACL), 2025
Qing Li
Fauzan Farooqui
Zongxiong Chen
Derui Zhu
Yuxia Wang
Congbo Ma
Chenyang Lyu
Fakhri Karray
262
4
0
30 May 2025
multivariateGPT: a decoder-only transformer for multivariate categorical and numeric data
multivariateGPT: a decoder-only transformer for multivariate categorical and numeric data
Andrew Loza
Jun Yup Kim
Shangzheng Song
Yihang Liu
Joseph J. Y. Sung
R Andrew Taylor
Dennis L. Shung
309
0
0
27 May 2025
Towards Identifiability of Interventional Stochastic Differential Equations
Towards Identifiability of Interventional Stochastic Differential Equations
Aaron Zweig
Zaikang Lin
Elham Azizi
David A. Knowles
383
1
0
21 May 2025
The Stochastic Occupation Kernel (SOCK) Method for Learning Stochastic Differential Equations
The Stochastic Occupation Kernel (SOCK) Method for Learning Stochastic Differential Equations
Michael L. Wells
Kamel Lahouel
Bruno Jedynak
264
0
0
16 May 2025
Riemannian Neural Geodesic Interpolant
Riemannian Neural Geodesic Interpolant
Jiawen Wu
Bingguang Chen
Yuyi Zhou
Qi Meng
Rongchan Zhu
Zhi-Ming Ma
206
0
0
22 Apr 2025
Defending Against Frequency-Based Attacks with Diffusion Models
Defending Against Frequency-Based Attacks with Diffusion Models
Fatemeh Amerehi
Patrick Healy
AAML
281
1
0
15 Apr 2025
Empirical risk minimization algorithm for multiclass classification of S.D.E. paths
Empirical risk minimization algorithm for multiclass classification of S.D.E. paths
Christophe Denis
Eddy Ella Mintsa
209
0
0
18 Mar 2025
FlowKac: An Efficient Neural Fokker-Planck solver using Temporal Normalizing Flows and the Feynman-Kac Formula
FlowKac: An Efficient Neural Fokker-Planck solver using Temporal Normalizing Flows and the Feynman-Kac Formula
Naoufal El Bekri
Lucas Drumetz
Franck Vermet
270
0
0
14 Mar 2025
In-Context Learning of Stochastic Differential Equations with Foundation Inference Models
In-Context Learning of Stochastic Differential Equations with Foundation Inference Models
Patrick Seifner
K. Cvejoski
David Berghaus
C. Ojeda
Ramses J. Sanchez
DiffM
291
6
0
26 Feb 2025
Filtered not Mixed: Stochastic Filtering-Based Online Gating for Mixture of Large Language Models
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
277
0
0
24 Feb 2025
Value Gradient Sampler: Sampling as Sequential Decision Making
Value Gradient Sampler: Sampling as Sequential Decision Making
Sangwoong Yoon
Himchan Hwang
Hyeokju Jeong
Dong Kyu Shin
Che-Sang Park
Sehee Kwon
Frank C. Park
394
1
0
18 Feb 2025
Neural Guided Diffusion Bridges
Neural Guided Diffusion Bridges
Gefan Yang
Frank van der Meulen
Stefan Sommer
DiffM
310
1
0
17 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
343
1
0
10 Feb 2025
Modeling Neural Networks with Privacy Using Neural Stochastic Differential Equations
Modeling Neural Networks with Privacy Using Neural Stochastic Differential Equations
Sanghyun Hong
Fan Wu
A. Gruber
Kookjin Lee
295
0
0
12 Jan 2025
ImageFlowNet: Forecasting Multiscale Image-Level Trajectories of Disease Progression with Irregularly-Sampled Longitudinal Medical Images
ImageFlowNet: Forecasting Multiscale Image-Level Trajectories of Disease Progression with Irregularly-Sampled Longitudinal Medical ImagesIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2024
Chen Liu
Ke Xu
Liangbo L. Shen
Guillaume Huguet
Zilong Wang
...
Danilo Bzdok
Jay Stewart
Jay C. Wang
L. V. Priore
Smita Krishnaswamy
483
0
0
08 Jan 2025
Deep Generalized Schr\"odinger Bridges: From Image Generation to Solving Mean-Field Games
Deep Generalized Schr\"odinger Bridges: From Image Generation to Solving Mean-Field Games
Guan-Horng Liu
Tianrong Chen
Evangelos A. Theodorou
238
0
0
31 Dec 2024
Improving the Noise Estimation of Latent Neural Stochastic Differential Equations
Improving the Noise Estimation of Latent Neural Stochastic Differential EquationsChaos (Chaos), 2024
Linus Heck
Maximilian Gelbrecht
Michael T. Schaub
Niklas Boers
DiffM
272
1
0
23 Dec 2024
Time-Causal VAE: Robust Financial Time Series Generator
Time-Causal VAE: Robust Financial Time Series Generator
Beatrice Acciaio
Stephan Eckstein
Songyan Hou
AI4TS
275
6
0
05 Nov 2024
Variational Neural Stochastic Differential Equations with Change Points
Variational Neural Stochastic Differential Equations with Change Points
Yousef El-Laham
Zhongchang Sun
Haibei Zhu
Tucker Balch
Svitlana Vyetrenko
346
1
0
01 Nov 2024
PACER: Physics Informed and Uncertainty Aware Climate Emulator
PACER: Physics Informed and Uncertainty Aware Climate Emulator
Hira Saleem
Flora Salim
Cormac Purcell
490
0
0
29 Oct 2024
Trajectory Flow Matching with Applications to Clinical Time Series Modeling
Trajectory Flow Matching with Applications to Clinical Time Series ModelingNeural Information Processing Systems (NeurIPS), 2024
Xi Zhang
Yuan Pu
Yuki Kawamura
Andrew Loza
Yoshua Bengio
Dennis L. Shung
Alexander Tong
OODAI4TSMedIm
325
16
0
28 Oct 2024
Utilizing Image Transforms and Diffusion Models for Generative Modeling
  of Short and Long Time Series
Utilizing Image Transforms and Diffusion Models for Generative Modeling of Short and Long Time SeriesNeural Information Processing Systems (NeurIPS), 2024
Ilan Naiman
Nimrod Berman
Itai Pemper
Idan Arbiv
Gal Fadlon
Omri Azencot
316
30
0
25 Oct 2024
Neuro-Symbolic Traders: Assessing the Wisdom of AI Crowds in Markets
Neuro-Symbolic Traders: Assessing the Wisdom of AI Crowds in Markets
Namid R Stillman
R. Baggott
AIFin
116
1
0
18 Oct 2024
Predicting time-varying flux and balance in metabolic systems using
  structured neural-ODE processes
Predicting time-varying flux and balance in metabolic systems using structured neural-ODE processes
Santanu Rathod
Pietro Lio
Xiao Zhang
64
1
0
18 Oct 2024
Geometric Trajectory Diffusion Models
Geometric Trajectory Diffusion ModelsNeural Information Processing Systems (NeurIPS), 2024
Jiaqi Han
Minkai Xu
Aaron Lou
Haotian Ye
Stefano Ermon
DiffM
266
12
0
16 Oct 2024
Parametric model reduction of mean-field and stochastic systems via
  higher-order action matching
Parametric model reduction of mean-field and stochastic systems via higher-order action matchingNeural Information Processing Systems (NeurIPS), 2024
Jules Berman
Tobias Blickhan
Benjamin Peherstorfer
591
4
0
15 Oct 2024
Efficient, Accurate and Stable Gradients for Neural ODEs
Efficient, Accurate and Stable Gradients for Neural ODEs
Sam McCallum
James Foster
449
8
0
15 Oct 2024
Latent Abstractions in Generative Diffusion Models
Latent Abstractions in Generative Diffusion Models
Giulio Franzese
Mattia Martini
Giulio Corallo
Paolo Papotti
Pietro Michiardi
DiffM
205
1
0
04 Oct 2024
Efficient Training of Neural Stochastic Differential Equations by Matching Finite Dimensional Distributions
Efficient Training of Neural Stochastic Differential Equations by Matching Finite Dimensional DistributionsInternational Conference on Learning Representations (ICLR), 2024
Jianxin Zhang
Josh Viktorov
Doosan Jung
Emily Pitler
DiffM
440
4
0
04 Oct 2024
Learning To Solve Differential Equation Constrained Optimization
  Problems
Learning To Solve Differential Equation Constrained Optimization Problems
Vincenzo Di Vito
M. Mohammadian
K. Baker
Ferdinando Fioretto
AI4CE
184
3
0
02 Oct 2024
Closed-Loop Long-Horizon Robotic Planning via Equilibrium Sequence Modeling
Closed-Loop Long-Horizon Robotic Planning via Equilibrium Sequence Modeling
Jinghan Li
Zhicheng Sun
Fei Li
740
2
0
02 Oct 2024
A Taxonomy of Loss Functions for Stochastic Optimal Control
A Taxonomy of Loss Functions for Stochastic Optimal Control
Carles Domingo-Enrich
268
8
0
01 Oct 2024
Neural Differential Appearance Equations
Neural Differential Appearance EquationsACM Transactions on Graphics (TOG), 2024
Chen Liu
Tobias Ritschel
249
1
0
23 Sep 2024
HJ-sampler: A Bayesian sampler for inverse problems of a stochastic
  process by leveraging Hamilton-Jacobi PDEs and score-based generative models
HJ-sampler: A Bayesian sampler for inverse problems of a stochastic process by leveraging Hamilton-Jacobi PDEs and score-based generative models
Tingwei Meng
Zongren Zou
Jérome Darbon
George Karniadakis
DiffM
304
3
0
15 Sep 2024
123
Next