Hongseok Yang

ORCID

Publication Activity (10 Years)

Years Active: 1998-2024
Publications (10 Years): 77

Top Venues

CoRR

NeurIPS

Proc. ACM Program. Lang.

ICML

Publications

Hyunsu Kim, Yegon Kim, Hongseok Yang, Juho Lee
Variational Partial Group Convolutions for Input-Aware Partial Equivariance of Rotations and Color-Shifts. CoRR (2024)
Nathanael L. Ackerman, Cameron E. Freer, Younesse Kaddar, Jacek Karwowski, Sean K. Moss, Daniel M. Roy, Sam Staton, Hongseok Yang
Probabilistic Programming Interfaces for Random Graphs: Markov Categories, Graphons, and Nominal Sets. Proc. ACM Program. Lang. 8 (POPL) (2024)
Wonyeol Lee, Xavier Rival, Hongseok Yang
Smoothness Analysis for Probabilistic Programs with Application to Optimised Variational Inference. Proc. ACM Program. Lang. 7 (POPL) (2023)
Seokin Seo, HyeongJoo Hwang, Hongseok Yang, Kee-Eung Kim
Regularized Behavior Cloning for Blocking the Leakage of Past Action Information. NeurIPS (2023)
Nathanael L. Ackerman, Cameron E. Freer, Younesse Kaddar, Jacek Karwowski, Sean K. Moss, Daniel M. Roy, Sam Staton, Hongseok Yang
Probabilistic programming interfaces for random graphs: Markov categories, graphons, and nominal sets. CoRR (2023)
Tien Dat Nguyen, Jinwoo Kim, Hongseok Yang, Seunghoon Hong
Learning Symmetrization for Equivariance with Orbit Distance Minimization. CoRR (2023)
Taeyoung Kim, Hongseok Yang
An Infinite-Width Analysis on the Jacobian-Regularised Training of a Neural Network. CoRR (2023)
Hyunsu Kim, Hyungi Lee, Hongseok Yang, Juho Lee
Regularizing Towards Soft Equivariance Under Mixed Symmetries. ICML (2023)
Hyunsu Kim, Hyungi Lee, Hongseok Yang, Juho Lee
Regularizing Towards Soft Equivariance Under Mixed Symmetries. CoRR (2023)
Francois Caron, Fadhel Ayed, Paul Jung, Hoil Lee, Juho Lee, Hongseok Yang
Over-parameterised Shallow Neural Networks with Asymmetrical Node Scaling: Global Convergence Guarantees and Feature Learning. CoRR (2023)
Sangho Lim, Eun-Gyeol Oh, Hongseok Yang
Learning Symmetric Rules with SATNet. NeurIPS (2022)
Geon-Hyeong Kim, Seokin Seo, Jongmin Lee, Wonseok Jeon, HyeongJoo Hwang, Hongseok Yang, Kee-Eung Kim
DemoDICE: Offline Imitation Learning with Supplementary Imperfect Demonstrations. ICLR (2022)
Hoil Lee, Fadhel Ayed, Paul Jung, Juho Lee, Hongseok Yang, François Caron
Deep neural networks with dependent weights: Gaussian Process mixture limit, heavy tails, sparsity and compressibility. CoRR (2022)
Geon-Hyeong Kim, Jongmin Lee, Youngsoo Jang, Hongseok Yang, Kee-Eung Kim
LobsDICE: Offline Imitation Learning from Observation via Stationary Distribution Correction Estimation. CoRR (2022)
Sangho Lim, Eun-Gyeol Oh, Hongseok Yang
Learning Symmetric Rules with SATNet. CoRR (2022)
Geon-Hyeong Kim, Jongmin Lee, Youngsoo Jang, Hongseok Yang, Kee-Eung Kim
LobsDICE: Offline Learning from Observation via Stationary Distribution Correction Estimation. NeurIPS (2022)
Wonyeol Lee, Xavier Rival, Hongseok Yang
Smoothness Analysis for Probabilistic Programs with Application to Optimised Variational Inference. CoRR (2022)
Hyungi Lee, Eunggu Yun, Hongseok Yang, Juho Lee
Scale Mixtures of Neural Network Gaussian Processes. ICLR (2022)
Hagit Attiya, Sebastian Burckhardt, Alexey Gotsman, Adam Morrison, Hongseok Yang, Marek Zawirski
Specification and space complexity of collaborative text editing. Theor. Comput. Sci. 855 (2021)
Gwonsoo Che, Hongseok Yang
Meta-Learning an Inference Algorithm for Probabilistic Programs. CoRR (2021)
Hyungi Lee, Eunggu Yun, Hongseok Yang, Juho Lee
Scale Mixtures of Neural Network Gaussian Processes. CoRR (2021)
Paul Jung, Hoil Lee, Jiho Lee, Hongseok Yang
α-Stable convergence of heavy-tailed infinitely-wide neural networks. CoRR (2021)
David Tolpin, Yuan Zhou, Tom Rainforth, Hongseok Yang
Probabilistic Programs with Stochastic Conditioning. ICML (2021)
Wonyeol Lee, Hangyeol Yu, Xavier Rival, Hongseok Yang
On Correctness of Automatic Differentiation for Non-Differentiable Functions. CoRR (2020)
Wonyeol Lee, Hangyeol Yu, Xavier Rival, Hongseok Yang
Towards verified stochastic variational inference for probabilistic programs. Proc. ACM Program. Lang. 4 (POPL) (2020)
David Tolpin, Yuan Zhou, Hongseok Yang
Bayesian Policy Search for Stochastic Domains. CoRR (2020)
Wonyeol Lee, Hangyeol Yu, Xavier Rival, Hongseok Yang
On Correctness of Automatic Differentiation for Non-Differentiable Functions. NeurIPS (2020)
Geon-Hyeong Kim, Youngsoo Jang, Hongseok Yang, Kee-Eung Kim
Variational Inference for Sequential Data with Future Likelihood Estimates. ICML (2020)
David Tolpin, Yuan Zhou, Hongseok Yang
Probabilistic Programs with Stochastic Conditioning. CoRR (2020)
Hyoungjin Lim, Gwonsoo Che, Wonyeol Lee, Hongseok Yang
Differentiable Algorithm for Marginalising Changepoints. AAAI (2020)
David Tolpin, Yuan Zhou, Hongseok Yang
Stochastically Differentiable Probabilistic Programs. CoRR (2020)
Yuan Zhou, Hongseok Yang, Yee Whye Teh, Tom Rainforth
Divide, Conquer, and Combine: a New Inference Strategy for Probabilistic Programs with Stochastic Support. ICML (2020)
Hyoungjin Lim, Gwonsoo Che, Wonyeol Lee, Hongseok Yang
Differentiable Algorithm for Marginalising Changepoints. CoRR (2019)
Yuan Zhou, Hongseok Yang, Yee Whye Teh, Tom Rainforth
Divide, Conquer, and Combine: a New Inference Strategy for Probabilistic Programs with Stochastic Support. CoRR (2019)
Kihong Heo, Hakjoo Oh, Hongseok Yang
Resource-aware program analysis via online abstraction coarsening. ICSE (2019)
Geon-hyeong Kim, Youngsoo Jang, Jongmin Lee, Wonseok Jeon, Hongseok Yang, Kee-Eung Kim
Trust Region Sequential Variational Inference. ACML (2019)
Yuan Zhou, Bradley J. Gram-Hansen, Tobias Kohn, Tom Rainforth, Hongseok Yang, Frank Wood
LF-PPL: A Low-Level First Order Probabilistic Programming Language for Non-Differentiable Models. CoRR (2019)
Wonyeol Lee, Hangyeol Yu, Xavier Rival, Hongseok Yang
Towards Verified Stochastic Variational Inference for Probabilistic Programs. CoRR (2019)
Yuan Zhou, Bradley J. Gram-Hansen, Tobias Kohn, Tom Rainforth, Hongseok Yang, Frank Wood
LF-PPL: A Low-Level First Order Probabilistic Programming Language for Non-Differentiable Models. AISTATS (2019)
Hongseok Yang
Some Semantic Issues in Probabilistic Programming Languages (Invited Talk). FSCD (2019)
Jan-Willem van de Meent, Brooks Paige, Hongseok Yang, Frank Wood
An Introduction to Probabilistic Programming. CoRR (2018)
Kihong Heo, Hakjoo Oh, Hongseok Yang, Kwangkeun Yi
Adaptive Static Analysis via Learning with Bayesian Optimization. ACM Trans. Program. Lang. Syst. 40 (4) (2018)
Sam Staton, Dario Stein, Hongseok Yang, Nathanael L. Ackerman, Cameron E. Freer, Daniel M. Roy
The Beta-Bernoulli process and algebraic effects. CoRR (2018)
Wonyeol Lee, Hangyeol Yu, Hongseok Yang
Reparameterization Gradient for Non-differentiable Models. NeurIPS (2018)
Kihong Heo, Hakjoo Oh, Hongseok Yang
Learning analysis strategies for octagon and context sensitivity from labeled data generated by static analyses. Formal Methods Syst. Des. 53 (2) (2018)
Sam Staton, Dario Stein, Hongseok Yang, Nathanael L. Ackerman, Cameron E. Freer, Daniel M. Roy
The Beta-Bernoulli process and algebraic effects. ICALP (2018)
Tom Rainforth, Robert Cornish, Hongseok Yang, Andrew Warrington
On Nesting Monte Carlo Estimators. ICML (2018)
Bradley Gram-Hansen, Yuan Zhou, Tobias Kohn, Hongseok Yang, Frank D. Wood
Discontinuous Hamiltonian Monte Carlo for Probabilistic Programs. CoRR (2018)
Wonyeol Lee, Hangyeol Yu, Hongseok Yang
Reparameterization Gradient for Non-differentiable Models. CoRR (2018)
Adam Scibior, Ohad Kammar, Matthijs Vákár, Sam Staton, Hongseok Yang, Yufei Cai, Klaus Ostermann, Sean K. Moss, Chris Heunen, Zoubin Ghahramani
Denotational validation of higher-order Bayesian inference. Proc. ACM Program. Lang. 2 (POPL) (2018)
Chris Heunen, Ohad Kammar, Sam Staton, Hongseok Yang
A Convenient Category for Higher-Order Probability Theory. CoRR (2017)
Hongseok Yang
Probabilistic Programming (Invited Talk). CONCUR (2017)
Kwonsoo Chae, Hakjoo Oh, Kihong Heo, Hongseok Yang
Automatically generating features for learning program analysis heuristics for C-like languages. Proc. ACM Program. Lang. 1 (OOPSLA) (2017)
Adam Scibior, Ohad Kammar, Matthijs Vákár, Sam Staton, Hongseok Yang, Yufei Cai, Klaus Ostermann, Sean K. Moss, Chris Heunen, Zoubin Ghahramani
Denotational validation of higher-order Bayesian inference. CoRR (2017)
Andrea Cerone, Alexey Gotsman, Hongseok Yang
Algebraic Laws for Weak Consistency. CoRR (2017)
Chris Heunen, Ohad Kammar, Sam Staton, Hongseok Yang
A convenient category for higher-order probability theory. LICS (2017)
Andrea Cerone, Alexey Gotsman, Hongseok Yang
Algebraic Laws for Weak Consistency. CONCUR (2017)
Hila Peleg, Sharon Shoham, Eran Yahav, Hongseok Yang
Symbolic automata for representing big code. Acta Informatica 53 (4) (2016)
David Tolpin, Jan-Willem van de Meent, Hongseok Yang, Frank D. Wood
Design and Implementation of Probabilistic Programming Language Anglican. CoRR (2016)
Hakjoo Oh, Wonchan Lee, Kihong Heo, Hongseok Yang, Kwangkeun Yi
Selective X-Sensitive Analysis Guided by Impact Pre-Analysis. ACM Trans. Program. Lang. Syst. 38 (2) (2016)
Sam Staton, Hongseok Yang, Chris Heunen, Ohad Kammar, Frank D. Wood
Semantics for probabilistic programming: higher-order functions, continuous distributions, and soft constraints. CoRR (2016)
Mahsa Najafzadeh, Alexey Gotsman, Hongseok Yang, Carla Ferreira, Marc Shapiro
The CISE tool: proving weakly-consistent applications correct. PaPoC@EuroSys (2016)
Radu Grigore, Hongseok Yang
Abstraction refinement guided by a learnt probabilistic model. POPL (2016)
Sam Staton, Hongseok Yang, Frank D. Wood, Chris Heunen, Ohad Kammar
Semantics for probabilistic programming: higher-order functions, continuous distributions, and soft constraints. LICS (2016)
Hagit Attiya, Sebastian Burckhardt, Alexey Gotsman, Adam Morrison, Hongseok Yang, Marek Zawirski
Specification and Complexity of Collaborative Text Editing. PODC (2016)
Kwonsoo Chae, Hakjoo Oh, Kihong Heo, Hongseok Yang
Automatically generating features for learning program analysis heuristics. CoRR (2016)
Alexey Gotsman, Hongseok Yang, Carla Ferreira, Mahsa Najafzadeh, Marc Shapiro
'Cause I'm strong enough: reasoning about consistency choices in distributed systems. POPL (2016)
Kihong Heo, Hakjoo Oh, Hongseok Yang
Learning a Variable-Clustering Strategy for Octagon from Labeled Data Generated by a Static Analysis. SAS (2016)
Mike Wu, Yura N. Perov, Frank D. Wood, Hongseok Yang
Spreadsheet Probabilistic Programming. CoRR (2016)
David Tolpin, Jan-Willem van de Meent, Hongseok Yang, Frank D. Wood
Design and Implementation of Probabilistic Programming Language Anglican. IFL (2016)
Andrea Cerone, Alexey Gotsman, Hongseok Yang
Transaction Chopping for Parallel Snapshot Isolation. DISC (2015)
Alexey Gotsman, Hongseok Yang
Composite Replicated Data Types. ESOP (2015)
Jan-Willem van de Meent, Hongseok Yang, Vikash Mansinghka, Frank D. Wood
Particle Gibbs with Ancestor Sampling for Probabilistic Programs. AISTATS (2015)
Jan-Willem van de Meent, Hongseok Yang, Vikash Mansinghka, Frank D. Wood
Particle Gibbs with Ancestor Sampling for Probabilistic Programs. CoRR (2015)
Hakjoo Oh, Hongseok Yang, Kwangkeun Yi
Learning a strategy for adapting a program analysis via bayesian optimisation. OOPSLA (2015)
Ghila Castelnuovo, Mayur Naik, Noam Rinetzky, Mooly Sagiv, Hongseok Yang
Modularity in Lattices: A Case Study on the Correspondence Between Top-Down and Bottom-Up Analysis. SAS (2015)
Radu Grigore, Hongseok Yang
Abstraction Refinement Guided by a Learnt Probabilistic Model. CoRR (2015)
Xin Zhang, Ravi Mangal, Mayur Naik, Hongseok Yang
Hybrid top-down and bottom-up interprocedural analysis. PLDI (2014)
Ravi Mangal, Mayur Naik, Hongseok Yang
A Correspondence between Two Approaches to Interprocedural Analysis in the Presence of Join. ESOP (2014)
Xin Zhang, Ravi Mangal, Radu Grigore, Mayur Naik, Hongseok Yang
On abstraction refinement for program analyses in Datalog. PLDI (2014)
Andrea Cerone, Alexey Gotsman, Hongseok Yang
Parameterised Linearisability. ICALP (2) (2014)
Sebastian Burckhardt, Alexey Gotsman, Hongseok Yang, Marek Zawirski
Replicated data types: specification, verification, optimality. POPL (2014)
Hakjoo Oh, Wonchan Lee, Kihong Heo, Hongseok Yang, Kwangkeun Yi
Selective context-sensitivity guided by impact pre-analysis. PLDI (2014)
Xin Zhang, Mayur Naik, Hongseok Yang
Finding optimum abstractions in parametric dataflow analysis. PLDI (2013)
Jan Schwinghammer, Lars Birkedal, François Pottier, Bernhard Reus, Kristian Støvring, Hongseok Yang
A step-indexed Kripke model of hidden state. Math. Struct. Comput. Sci. 23 (1) (2013)
Hila Peleg, Sharon Shoham, Eran Yahav, Hongseok Yang
Symbolic Automata for Static Specification Mining. SAS (2013)
Alexey Gotsman, Noam Rinetzky, Hongseok Yang
Verifying Concurrent Memory Reclamation Algorithms with Grace. ESOP (2013)
Alexey Gotsman, Hongseok Yang
Modular verification of preemptive OS kernels. J. Funct. Program. 23 (4) (2013)
Thomas Dinsdale-Young, Lars Birkedal, Philippa Gardner, Matthew J. Parkinson, Hongseok Yang
Views: compositional reasoning for concurrent programs. POPL (2013)
Alexey Gotsman, Hongseok Yang
Linearizability with Ownership Transfer. Log. Methods Comput. Sci. 9 (3) (2013)
Oukseh Lee, Hongseok Yang, Rasmus Petersen
A divide-and-conquer approach for analysing overlaid data structures. Formal Methods Syst. Des. 41 (1) (2012)
Mayur Naik, Hongseok Yang, Ghila Castelnuovo, Mooly Sagiv
Abstractions from tests. POPL (2012)
Saswat Anand, Mayur Naik, Mary Jean Harrold, Hongseok Yang
Automated concolic testing of smartphone apps. SIGSOFT FSE (2012)
Alexey Gotsman, Hongseok Yang
Linearizability with Ownership Transfer. CONCUR (2012)
Alexey Gotsman, Madanlal Musuvathi, Hongseok Yang
Show No Weakness: Sequentially Consistent Specifications of TSO Libraries. DISC (2012)
Jacob Thamsborg, Lars Birkedal, Hongseok Yang
Two for the Price of One: Lifting Separation Logic Assertions Log. Methods Comput. Sci. 8 (3) (2012)
Sebastian Burckhardt, Alexey Gotsman, Madanlal Musuvathi, Hongseok Yang
Concurrent Library Correctness on the TSO Memory Model. ESOP (2012)
Alexey Gotsman, Hongseok Yang
Liveness-Preserving Atomicity Abstraction. ICALP (2) (2011)
Lars Birkedal, Bernhard Reus, Jan Schwinghammer, Kristian Støvring, Jacob Thamsborg, Hongseok Yang
Step-indexed kripke models over recursive worlds. POPL (2011)
Oukseh Lee, Hongseok Yang, Rasmus Petersen
Program Analysis for Overlaid Data Structures. CAV (2011)

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Publication Activity (10 Years)

Top Topics

Top Venues

Hongseok Yang