Patrick Kidger

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All published works

Action	Title	Year	Authors
+ PDF Chat	Single-seed generation of Brownian paths and integrals for adaptive and high order SDE solvers	2024	Andraž Jelinčič James Foster Patrick Kidger
+ PDF Chat	Optimistix: modular optimisation in JAX and Equinox	2024	Jason Rader Terry Lyons Patrick Kidger
+	Lineax: unified linear solves and linear least-squares in JAX and Equinox	2023	Jason Rader Terry Lyons Patrick Kidger
+	On Neural Differential Equations	2022	Patrick Kidger
+	Efficient and Accurate Gradients for Neural SDEs	2021	Patrick Kidger James Foster Xuechen Li Terry Lyons
+	Equinox: neural networks in JAX via callable PyTrees and filtered transformations.	2021	Patrick Kidger Cristian Garcia
+	Efficient and Accurate Gradients for Neural SDEs	2021	Patrick Kidger James Foster Xuechen Li Terry Lyons
+	"Hey, that's not an ODE'": Faster ODE Adjoints with 12 Lines of Code	2021	Patrick Kidger Ricky T. Q. Chen Terry Lyons
+	Signatory: differentiable computations of the signature and logsignature transforms, on both CPU and GPU	2021	Patrick Kidger Terry Lyons
+	Neural SDEs as Infinite-Dimensional GANs	2021	Patrick Kidger James Foster Xuechen Li Harald Oberhauser Terry Lyons
+	Neural Controlled Differential Equations for Online Prediction Tasks	2021	James Morrill Patrick Kidger Lingyi Yang Terry Lyons
+	Equinox: neural networks in JAX via callable PyTrees and filtered transformations	2021	Patrick Kidger Cristian Garcia
+	Efficient and Accurate Gradients for Neural SDEs	2021	Patrick Kidger James Foster Xuechen Li Terry Lyons
+	Neural SDEs as Infinite-Dimensional GANs	2021	Patrick Kidger James Foster Xuechen Li Harald Oberhauser Terry Lyons
+	"Hey, that's not an ODE": Faster ODE Adjoints via Seminorms	2020	Patrick Kidger Ricky T. Q. Chen Terry Lyons
+	A Generalised Signature Method for Time Series	2020	James Morrill Adeline Fermanian Patrick Kidger Terry Lyons
+	A Generalised Signature Method for Time Series	2020	J.L. Morrill Adeline Fermanian Patrick Kidger Terry Lyons
+	A Generalised Signature Method for Multivariate Time Series Feature Extraction	2020	James Morrill Adeline Fermanian Patrick Kidger Terry Lyons
+	Signatory: differentiable computations of the signature and logsignature transforms, on both CPU and GPU	2020	Patrick Kidger Terry Lyons
+	The degree-$(n+1)$ polynomials are the most difficult $C^{\,n + 1}$ functions to uniformly approximate with degree-$n$ polynomials	2020	Patrick Kidger
+	Neural Controlled Differential Equations for Irregular Time Series	2020	Patrick Kidger James Morrill James Foster Terry Lyons
+	Generalised Interpretable Shapelets for Irregular Time Series	2020	Patrick Kidger James Morrill Terry Lyons
+	Neural Rough Differential Equations for Long Time Series	2020	James Morrill Cristopher Salvi Patrick Kidger James Foster Terry Lyons
+	"Hey, that's not an ODE": Faster ODE Adjoints via Seminorms	2020	Patrick Kidger Tian Qi Chen Terry Lyons
+	A Generalised Signature Method for Multivariate Time Series Feature Extraction	2020	J.L. Morrill Adeline Fermanian Patrick Kidger Terry Lyons
+	Universal Approximation with Deep Narrow Networks	2019	Patrick Kidger Terry Lyons
+	Deep Signatures	2019	Patric Bonnier Patrick Kidger Imanol Pérez Arribas Cristopher Salvi Terry Lyons
+	Deep Signature Transforms	2019	Patric Bonnier Patrick Kidger Imanol Pérez Arribas Cristopher Salvi Terry Lyons
+	Universal Approximation with Deep Narrow Networks	2019	Patrick Kidger Terry Lyons

Common Coauthors

Coauthor	Papers Together
Terry Lyons	24
James Morrill	6
James Foster	5
Xuechen Li	4
Cristopher Salvi	3
Adeline Fermanian	3
James Foster	3
Cristian Garcia	2
J.L. Morrill	2
Ricky T. Q. Chen	2
Harald Oberhauser	2
Imanol Pérez Arribas	2
Patric Bonnier	2
Jason Rader	2
Xuechen Li	1
Adeline Fermanian	1
Lingyi Yang	1
Tian Qi Chen	1
Andraž Jelinčič	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	Adam: A Method for Stochastic Optimization	2014	Diederik P. Kingma Jimmy Ba	9
+	Kernels for sequentially ordered data	2019	Franz J. Király Harald Oberhauser	8
+	Learning stochastic differential equations using RNN with log signature features	2019	Shujian Liao Terry Lyons Weixin Yang Hao Ni	7
+	Neural ordinary differential equations	2018	Ricky T. Q. Chen Yulia Rubanova Jesse Bettencourt David Duvenaud	7
+	A Primer on the Signature Method in Machine Learning	2016	Ilya Chevyrev Andrey Kormilitzin	6
+	Differential Equations Driven by Rough Paths	2007	Terence J. Lyons Michael Caruana Thierry Lévy École d'été de probabilités de Saint-Flour	6
+ PDF Chat	Differential equations driven by rough signals	1998	Terry Lyons	6
+	Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition	2018	Pete Warden	6
+	Signatory: differentiable computations of the signature and logsignature transforms, on both CPU and GPU	2020	Patrick Kidger Terry Lyons	6
+ PDF Chat	Uniqueness for the signature of a path of bounded variation and the reduced path group	2010	Ben Hambly Terry Lyons	5
+ PDF Chat	A signature-based machine learning model for distinguishing bipolar disorder and borderline personality disorder	2018	Imanol Pérez Arribas Guy M. Goodwin John Geddes Terry Lyons Kate Saunders	5
+	Embedding and learning with signatures	2019	Adeline Fermanian	5
+	Learning from the past, predicting the statistics for the future, learning an evolving system	2013	Daniel Levin Terry Lyons Hao Ni	5
+	Rough paths, Signatures and the modelling of functions on streams	2014	Terry Lyons	5
+ PDF Chat	DeepWriterID: An End-to-End Online Text-Independent Writer Identification System	2016	Weixin Yang Lianwen Jin Manfei Liu	5
+	The iisignature library: efficient calculation of iterated-integral signatures and log signatures.	2018	Jeremy Reizenstein Benjamin Graham	5
+	PyTorch: An Imperative Style, High-Performance Deep Learning Library	2019	Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury Gregory Chanan Trevor Killeen Zeming Lin Natalia Gimelshein Luca Antiga	4
+ PDF Chat	Recurrent Neural Networks for Multivariate Time Series with Missing Values	2018	Zhengping Che Sanjay Purushotham Kyunghyun Cho David Sontag Yan Liu	4
+	Application of the Signature Method to Pattern Recognition in the CEQUEL Clinical Trial	2016	Andrey Kormilitzin Kate Saunders Paul J. Harrison John Geddes Terry Lyons	4
+	Variational Gaussian Processes with Signature Covariances.	2019	Csaba Tóth Harald Oberhauser	4
+	Generalised Interpretable Shapelets for Irregular Time Series	2020	Patrick Kidger James Morrill Terry Lyons	4
+	GRU-ODE-Bayes: Continuous Modeling of Sporadically-Observed Time Series	2019	Edward De Brouwer Jaak Simm Ádám Arany Yves Moreau	3
+ PDF Chat	An Optimal Polynomial Approximation of Brownian Motion	2020	James Foster Terry Lyons Harald Oberhauser	3
+	Neural Stochastic Differential Equations: Deep Latent Gaussian Models in the Diffusion Limit	2019	Belinda Tzen Maxim Raginsky	3
+	Multidimensional Stochastic Processes as Rough Paths	2010	Peter K. Friz Nicolas Victoir	3
+	The UEA multivariate time series classification archive, 2018.	2018	Anthony Bagnall Hoang Anh Dau Jason Lines Michael Flynn James Large Aaron Bostrom Paul Southam Eamonn Keogh	3
+	Generative Moment Matching Networks	2015	Yujia Li Kevin Swersky Rich Zemel	3
+	Neural Rough Differential Equations for Long Time Series	2020	James Morrill Cristopher Salvi Patrick Kidger James Foster Terry Lyons	3
+	Scalable Gradients and Variational Inference for Stochastic Differential Equations	2019	Xuechen Li Ting‐Kam Leonard Wong Ricky T. Q. Chen David Duvenaud	3
+	Derivatives pricing using signature payoffs	2018	Imanol Pérez Arribas	3
+	Dissecting Neural ODEs	2020	Stefano Massaroli Michael Poli Jinkyoo Park Atsushi Yamashita Hajime Asama	3
+	Stochastic Normalizing Flows	2020	Liam Hodgkinson Christopher van der Heide Fred Roosta Michael W. Mahoney	3
+	A Generalised Signature Method for Multivariate Time Series Feature Extraction	2020	James Morrill Adeline Fermanian Patrick Kidger Terry Lyons	3
+	Neural Jump Stochastic Differential Equations	2019	Junteng Jia Austin R. Benson	2
+	Scikit-learn: Machine Learning in Python	2012	Fabián Pedregosa Gaël Varoquaux Alexandre Gramfort Vincent Michel Bertrand Thirion Olivier Grisel Mathieu Blondel Peter Prettenhofer Ron J. Weiss Vincent Dubourg	2
+	Free Lie Algebras	1993	Christophe Reutenauer	2
+ PDF Chat	Standard Lyndon bases of Lie algebras and enveloping algebras	1995	Pierre Lalonde Arun Ram	2
+	ANODE: Unconditionally Accurate Memory-Efficient Gradients for Neural ODEs	2019	Amir Gholaminejad Kurt Keutzer George Biros	2
+	The Unusual Effectiveness of Averaging in GAN Training	2018	Yasin Yazıcı Chuan-Sheng Foo Stefan Winkler Kim–Hui Yap Georgios Piliouras Vijay Chandrasekhar	2
+	Combinatorics on words	1984	M. Lothaire	2
+	Spectral Normalization for Generative Adversarial Networks	2018	Takeru Miyato Toshiki Kataoka Masanori Koyama Yuichi Yoshida	2
+ PDF Chat	Universal Differential Equations for Scientific Machine Learning	2020	Christopher Rackauckas Yingbo Ma Carl Julius Martensen Collin Warner Kirill Zubov Rohit Supekar Dominic J. Skinner Ali Ramadhan Alan Edelman	2
+	Neural SDE: Stabilizing Neural ODE Networks with Stochastic Noise	2019	Xuanqing Liu Tesi Xiao Si Si Cao Qin Sanjiv Kumar Cho‐Jui Hsieh	2
+	A kernel two-sample test	2012	Arthur Gretton Karsten Borgwardt Malte J. Rasch Bernhard Schölkopf Alexander J. Smola	2
+	Should we really use post-hoc tests based on mean-ranks?	2015	Alessio Benavoli Giorgio Corani Francesca Mangili	2
+	Dimension-free Euler estimates of rough differential equations	2013	Youness Boutaib Lajos Gergely Gyurkó Terry Lyons Danyu Yang	2
+	Interpolation-Prediction Networks for Irregularly Sampled Time Series	2019	Satya Narayan Shukla Benjamin M. Marlin	2
+	ANODE: Unconditionally Accurate Memory-Efficient Gradients for Neural ODEs	2019	Amir Gholami Kurt Keutzer George Biros	2
+	Pathwise approximation of SDEs by coupling piecewise abelian rough paths	2015	Guy Flint Terry Lyons	2
+	Deep Signature Transforms	2019	Patric Bonnier Patrick Kidger Imanol Pérez Arribas Cristopher Salvi Terry Lyons	2