Saurabh Johri

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All published works

Action	Title	Year	Authors
+	Learning medical triage from clinicians using Deep Q-Learning.	2020	Albert Buchard Baptiste Bouvier Giulia Prando Rory Beard Michail Livieratos Dan Busbridge Daniel H. Thompson Jonathan G. Richens Yuanzhao Zhang Adam Baker
+	Masking schemes for universal marginalisers	2020	Divya Gautam María Lomelí Kostis Gourgoulias Daniel H. Thompson Saurabh Johri
+	Learning medical triage from clinicians using Deep Q-Learning	2020	Albert Buchard Baptiste Bouvier Giulia Prando Rory Beard Michail Livieratos Dan Busbridge Daniel B. Thompson Jonathan G. Richens Yuanzhao Zhang Adam Baker
+	Leveraging directed causal discovery to detect latent common causes.	2019	Ciarán M. Lee Christopher D. Hart Jonathan G. Richens Saurabh Johri
+	Counterfactual diagnosis.	2019	Jonathan G. Richens Ciaran M. Lee Saurabh Johri
+	Universal Marginaliser for Deep Amortised Inference for Probabilistic Programs	2019	Robert Walecki Kostis Gourgoulias Adam Baker Chris Hart Chris Lucas Max Zwiessele Albert Buchard María Lomelí Yura Perov Saurabh Johri
+	MultiVerse: Causal Reasoning using Importance Sampling in Probabilistic Programming	2019	Yura Perov Logan Graham Kostis Gourgoulias Jonathan G. Richens Ciarán M. Lee Adam Baker Saurabh Johri
+	Counterfactual diagnosis	2019	Jonathan G. Richens Ciaran M. Lee Saurabh Johri
+	Leveraging directed causal discovery to detect latent common causes	2019	Ciarán M. Lee Christopher Hart Jonathan G. Richens Saurabh Johri
+	A comparative study of artificial intelligence and human doctors for the purpose of triage and diagnosis	2018	Salman Razzaki Adam Baker Yura Perov Katherine Middleton Janie Baxter Daniel Mullarkey Davinder Sangar Michael Taliercio Mobasher Butt Azeem Majeed
+	Universal Marginalizer for Amortised Inference and Embedding of Generative Models	2018	Robert Walecki Albert Buchard Kostis Gourgoulias Chris Hart María Lomelí Alexandre K. W. Navarro Max Zwiessele Yura Perov Saurabh Johri
+	A comparative study of artificial intelligence and human doctors for the purpose of triage and diagnosis	2018	Salman Razzaki Adam Baker Yura Perov Katherine Middleton Janie Baxter Daniel J. Mullarkey Davinder Sangar Michael Taliercio Mobasher Butt Azeem Majeed
+	A Universal Marginalizer for Amortized Inference in Generative Models.	2017	Laura Douglas Iliyan Zarov Konstantinos Gourgoulias Chris Lucas Chris Hart Adam Baker Maneesh Sahani Yura Perov Saurabh Johri
+	A Universal Marginalizer for Amortized Inference in Generative Models	2017	Laura Douglas Iliyan Zarov Konstantinos Gourgoulias Chris Lucas Chris Hart Adam Baker Maneesh Sahani Yura Perov Saurabh Johri

Common Coauthors

Coauthor	Papers Together
Yura Perov	9
Jonathan G. Richens	7
Kostis Gourgoulias	6
Adam Baker	5
Albert Buchard	4
Chris Hart	3
Ciarán M. Lee	3
Adam Baker	3
María Lomelí	3
Michail Livieratos	2
Baptiste Bouvier	2
Michael Taliercio	2
Megan Mahoney	2
Azeem Majeed	2
Yuanzhao Zhang	2
Katherine Middleton	2
Max Zwiessele	2
Iliyan Zarov	2
Maneesh Sahani	2
Laura Douglas	2
Davinder Sangar	2
Dan Busbridge	2
Janie Baxter	2
Rory Beard	2
Robert Walecki	2
Konstantinos Gourgoulias	2
Arnold DoRosario	2
Chris Lucas	2
Giulia Prando	2
Ciaran M. Lee	2
Daniel H. Thompson	1
Mobasher Butt	1
Chris Lucas	1
Chris Hart	1
Salman Razzaki	1
Logan Graham	1
Christopher D. Hart	1
Alexandre K. W. Navarro	1
Daniel B. Thompson	1
Mobasher Butt	1
Salman Razzaki	1
Daniel Mullarkey	1
Christopher Hart	1
Daniel J. Mullarkey	1
Daniel H. Thompson	1
Divya Gautam	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	Deep Amortized Inference for Probabilistic Programs	2016	Daniel Ritchie Paul Horsfall Noah D. Goodman	3
+	MADE: Masked Autoencoder for Distribution Estimation	2015	Mathieu Germain Karol Gregor Iain Murray Hugo Larochelle	3
+ PDF Chat	Using synthetic data to train neural networks is model-based reasoning	2017	Tuan Anh Le Atılım Güneş Baydin Robert Zinkov Frank Wood	3
+	Applications of Probabilistic Programming (Master's thesis, 2015)	2016	Yura Perov	2
+	Counterfactual diagnosis.	2019	Jonathan G. Richens Ciaran M. Lee Saurabh Johri	2
+	An empirical analysis of likelihood-weighting simulation on a large, multiply connected medical belief network	1991	Michael Shwe Gregory F. Cooper	2
+	Inference Compilation and Universal Probabilistic Programming	2016	Tuan Anh Le Atılım Güneş Baydin Frank Wood	2
+ PDF Chat	AIS-BN: An Adaptive Importance Sampling Algorithm for Evidential Reasoning in Large Bayesian Networks	2000	J.-J. Cheng Marek J. Drużdżel	2
+	Data-driven Sequential Monte Carlo in Probabilistic Programming	2015	Yura Perov Tuan Anh Le Frank Wood	2
+	Universal Marginalizer for Amortised Inference and Embedding of Generative Models	2018	Robert Walecki Albert Buchard Kostis Gourgoulias Chris Hart María Lomelí Alexandre K. W. Navarro Max Zwiessele Yura Perov Saurabh Johri	2
+	Learning about an exponential amount of conditional distributions	2019	Mohamed Ishmael Belghazi Maxime Oquab Yann LeCun David López-Paz	2
+	Pyro: Deep Universal Probabilistic Programming	2018	Eli Bingham Jonathan P. Chen Martin Jankowiak Fritz Obermeyer Neeraj Pradhan Theofanis Karaletsos Rohit Singh Paul Szerlip Paul Horsfall Noah D. Goodman	2
+	A Compilation Target for Probabilistic Programming Languages	2014	Brooks Paige Frank Wood	1
+ PDF Chat	Quantum Common Causes and Quantum Causal Models	2017	John-Mark A. Allen Jonathan Barrett Dominic Horsman Ciarán M. Lee Robert W. Spekkens	1
+	Causal Inference via Algebraic Geometry: Feasibility Tests for Functional Causal Structures with Two Binary Observed Variables	2017	Ciarán M. Lee Robert W. Spekkens	1
+	Counterfactual Fairness	2017	Matt J. Kusner Joshua R. Loftus Chris Russell Ricardo Silva	1
+	Reliable Decision Support using Counterfactual Models	2017	Peter Schulam Suchi Saria	1
+	Local Rule-Based Explanations of Black Box Decision Systems.	2018	Riccardo Guidotti Anna Monreale Salvatore Ruggieri Dino Pedreschi Franco Turini Fosca Giannotti	1
+	An Introduction to Probabilistic Programming	2018	Jan-Willem van de Meent Brooks Paige Hongseok Yang Frank Wood	1
+	Simple, Distributed, and Accelerated Probabilistic Programming	2018	Dustin Tran Matthew D. Hoffman Dave Moore Christopher Suter Vasudevan Srinivas Alexey Radul Matthew Johnson Rif A. Saurous	1
+ PDF Chat	We Are Not Your Real Parents: Telling Causal from Confounded using MDL	2019	David Kaltenpoth Jilles Vreeken	1
+	Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift	2015	Sergey Ioffe Christian Szegedy	1
+	Counterfactual Risk Minimization: Learning from Logged Bandit Feedback	2015	Adith Swaminathan Thorsten Joachims	1
+	Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations	2018	Francesco Locatello Stefan Bauer Mario Lučić Gunnar Rätsch Sylvain Gelly Bernhard Schölkopf Olivier Bachem	1
+	Design and Implementation of Probabilistic Programming Language Anglican	2016	David Tolpin Jan Willem van de Meent Hongseok Yang Frank Wood	1
+	Church: a language for generative models	2012	Noah D. Goodman Vikash K. Mansinghka Daniel M. Roy Keith Bonawitz Joshua B. Tenenbaum	1
+	MADE: Masked Autoencoder for Distribution Estimation	2015	Mathieu Germain Karol Gregor Iain Murray Hugo Larochelle	1
+	Attention is All you Need	2017	Ashish Vaswani Noam Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan N. Gomez Łukasz Kaiser Illia Polosukhin	1
+	Simple, Distributed, and Accelerated Probabilistic Programming	2018	Dustin Tran Matthew W. Hoffman Dave Moore Christopher Suter Vasudevan Srinivas Alexey Radul	1
+	Self-Normalizing Neural Networks	2017	Günter Klambauer Thomas Unterthiner Andreas Mayr Sepp Hochreiter	1
+	Prioritized Experience Replay	2015	Tom Schaul John Quan Ioannis Antonoglou David Silver	1
+	Woulda, Coulda, Shoulda: Counterfactually-Guided Policy Search	2018	Lars Buesing Théophane Weber Yori Zwólš Nicolas Heess Sébastien Racanière Arthur Guez Jean-Baptiste Lespiau	1
+ PDF Chat	Counterfactual Learning from Bandit Feedback under Deterministic Logging : A Case Study in Statistical Machine Translation	2017	Carolin Lawrence Artem Sokolov Stefan Riezler	1
+	Causal Inference via Kernel Deviance Measures	2018	Jovana Mitrovic Dino Sejdinović Yee Whye Teh	1
+	Learning Representations for Counterfactual Inference	2016	Fredrik Johansson Uri Shalit David Sontag	1
+ PDF Chat	Theoretical Impediments to Machine Learning With Seven Sparks from the Causal Revolution	2018	Judea Pearl	1
+	Reinforcement Learning in Healthcare: A Survey	2019	Chao Yu Jiming Liu Shamim Nemati	1
+	MultiVerse: Causal Reasoning using Importance Sampling in Probabilistic Programming	2019	Yura Perov Logan Graham Kostis Gourgoulias Jonathan G. Richens Ciarán M. Lee Adam Baker Saurabh Johri	1
+ PDF Chat	Offline A/B Testing for Recommender Systems	2018	Alexandre Gilotte Clément Calauzènes Thomas Nedelec Alexandre Abraham Simon Dollé	1
+ PDF Chat	The Inflation Technique for Causal Inference with Latent Variables	2019	Elie Wolfe Robert W. Spekkens T. A. Fritz	1
+ PDF Chat	Device-independent certification of non-classical joint measurements via causal models	2019	Ciarán M. Lee	1
+ PDF Chat	Variational Probabilistic Inference and the QMR-DT Network	1999	Tommi Jaakkola Michael I. Jordan	1
+ PDF Chat	Counterfactual Estimation and Optimization of Click Metrics in Search Engines	2015	Lihong Li Shunbao Chen Jim Kleban Ankur Gupta	1
+	Counterfactual Explanations without Opening the Black Box: Automated Decisions and the Gdpr	2018	Sandra Wachter Brent Mittelstadt Chris Russell	1
+	None	2001	Radford M. Neal	1
+	Loopy belief propagation for approximate inference: an empirical study	1999	Kevin P. Murphy Yair Weiss Michael I. Jordan	1
+	Towards a Learning Theory of Cause-Effect Inference	2015	David López-Paz Krikamol Muandet Bernhard Schölkopf Ilya Tolstikhin	1
+	Identifying confounders using additive noise models	2009	Dominik Janzing Jonas Peters Joris M. Mooij Bernhard Schölkopf	1
+	Venture: a higher-order probabilistic programming platform with programmable inference	2014	Vikash K. Mansinghka Daniel Selsam Yura Perov	1
+	Distinguishing cause from effect using observational data: methods and benchmarks	2016	Joris M. Mooij Jonas Peters Dominik Janzing Jakob Zscheischler Bernhard Schölkopf	1