Luke Ong

53 papers A* 11A 5C 2Journal 32Unranked 2
YearRankTypeTitle / Venue / Authors
2026 A* conf
Conformal Prediction Meets Long-tail Classification.
AAAI
Shuqi Liu, Jianguo Huang, Luke Ong
2026 J jnl
When More Experts Hurt: Underfitting in Multi-Expert Learning to Defer.
CoRR
Shuqi Liu, Yuzhou Cao, Lei Feng, Bo An, Luke Ong
2025 J jnl
Comparative Analysis of Barrier-like Function Methods for Reach-Avoid Verification in Stochastic Discrete-Time Systems.
CoRR
Zhipeng Cao, Peixin Wang, Luke Ong, Dorde Zikelic, Dominik Wagner, Bai Xue
2025 J jnl
Conformal Prediction Meets Long-tail Classification.
CoRR
Shuqi Liu, Jianguo Huang, Luke Ong
2025 J jnl
Open Problems in Machine Unlearning for AI Safety.
CoRR
Fazl Barez, Tingchen Fu, Ameya Prabhu, Stephen Casper, Amartya Sanyal, Adel Bibi, Aidan O'Gara, Robert Kirk, Ben Bucknall, Timothy Fist, Luke Ong, Philip Torr, Kwok-Yan Lam, Robert Trager, David Krueger, Sören Mindermann, José Hernández-Orallo, Mor Geva, Yarin Gal
2025 J jnl
PAC One-Step Safety Certification for Black-Box Discrete-Time Stochastic Systems.
CoRR
Taoran Wu, Dominik Wagner, Jingduo Pan, Luke Ong, Arvind Easwaran, Bai Xue
2025 J jnl
Refined Barrier Conditions for Finite-Time Safety and Reach-Avoid Guarantees in Stochastic Systems.
CoRR
Bai Xue, Luke Ong, Dominik Wagner, Peixin Wang
2025 J jnl
Reinforcement Learning with ω-Regular Objectives and Constraints.
CoRR
Dominik Wagner, Leon Witzman, Luke Ong
2025 J jnl
Safety-Biased Policy Optimisation: Towards Hard-Constrained Reinforcement Learning via Trust Regions.
CoRR
Ankit Kanwar, Dominik Wagner, Luke Ong
2025 J jnl
The Singapore Consensus on Global AI Safety Research Priorities.
CoRR
Yoshua Bengio, Tegan Maharaj, Luke Ong, Stuart Russell, Dawn Song, Max Tegmark, Lan Xue, Ya-Qin Zhang, Stephen Casper, Wan Sie Lee, Sören Mindermann, Vanessa Wilfred, Vidhisha Balachandran, Fazl Barez, Michael Belinsky, Imane Bello, Malo Bourgon, Mark Brakel, Siméon Campos, Duncan Cass-Beggs, Jiahao Chen, Rumman Chowdhury, Kuan Chua Seah, Jeff Clune, Juntao Dai, Agnès Delaborde, Nouha Dziri, Francisco Eiras, Joshua Engels, Jinyu Fan, Adam Gleave, Noah Goodman, Fynn Heide, Johannes Heidecke, Dan Hendrycks, Cyrus Hodes, Bryan Low Kian Hsiang, Minlie Huang, Sami Jawhar, Wang Jingyu, Adam Tauman Kalai, Meindert Kamphuis, Mohan S. Kankanhalli, Subhash Kantamneni, Mathias Bonde Kirk, Thomas Kwa, Jeffrey Ladish, Kwok-Yan Lam, Wan Lee Sie, Taewhi Lee, Xiaojian Li, Jiajun Liu, Chaochao Lu, Yifan Mai, Richard Mallah, Julian Michael, Nick Moës, Simon Möller, Kihyuk Nam, Kwan Yee Ng, Mark Nitzberg, Besmira Nushi, Seán Ó hÉigeartaigh, Alejandro Ortega, Pierre Peigné, James Petrie, Benjamin Prud'homme, Reihaneh Rabbany, Nayat Sánchez-Pi, Sarah Schwettmann, Buck Shlegeris, Saad Siddiqui, Aradhana Sinha, Martín Soto, Cheston Tan, Dong Ting, William-Chandra Tjhi, Robert Trager, Brian Tse, Anthony Tung K. H., John Willes, Denise Wong, Wei Xu, Rongwu Xu, Yi Zeng, HongJiang Zhang, Djordje Zikelic
2025 A* conf
Towards Interpreting Visual Information Processing in Vision-Language Models.
ICLR
Clement Neo, Luke Ong, Philip Torr, Mor Geva, David Krueger, Fazl Barez
2024 A conf
Beyond Bayesian Model Averaging over Paths in Probabilistic Programs with Stochastic Support.
AISTATS
Tim Reichelt, Luke Ong, Tom Rainforth
2024 A conf
Diagonalisation SGD: Fast & Convergent SGD for Non-Differentiable Models via Reparameterisation and Smoothing.
AISTATS
Dominik Wagner, Basim Khajwal, Luke Ong
2024 A* conf
Reinforcement Learning with LTL and ω-Regular Objectives via Optimality-Preserving Translation to Average Rewards.
NeurIPS
Xuan-Bach Le, Dominik Wagner, Leon Witzman, Alexander Rabinovich, Luke Ong
2024 J jnl
Reinforcement Learning with LTL and ω-Regular Objectives via Optimality-Preserving Translation to Average Rewards.
CoRR
Xuan-Bach Le, Dominik Wagner, Leon Witzman, Alexander Rabinovich, Luke Ong
2024 J jnl
Towards Interpreting Visual Information Processing in Vision-Language Models.
CoRR
Clement Neo, Luke Ong, Philip Torr, Mor Geva, David Krueger, Fazl Barez
2024 J jnl
Unifying Qualitative and Quantitative Safety Verification of DNN-Controlled Systems.
CoRR
Dapeng Zhi, Peixin Wang, Si Liu, Luke Ong, Min Zhang
2023 J jnl
Beyond Bayesian Model Averaging over Paths in Probabilistic Programs with Stochastic Support.
CoRR
Tim Reichelt, Luke Ong, Tom Rainforth
2023 J jnl
Exact Bayesian Inference on Discrete Models via Probability Generating Functions: A Probabilistic Programming Approach.
CoRR
Fabian Zaiser, Andrzej S. Murawski, Luke Ong
2023 J jnl
Rethinking Variational Inference for Probabilistic Programs with Stochastic Support.
CoRR
Tim Reichelt, Luke Ong, Tom Rainforth
2023 J jnl
Template-Based Static Posterior Inference for Bayesian Probabilistic Programming.
CoRR
Peixin Wang, Hongfei Fu, Tengshun Yang, Guanyan Li, Luke Ong
2022 A conf
Expectation programming: Adapting probabilistic programming systems to estimate expectations efficiently.
UAI
Tim Reichelt, Adam Golinski, Luke Ong, Tom Rainforth
2022 J jnl
Guaranteed Bounds for Posterior Inference in Universal Probabilistic Programming.
CoRR
Raven Beutner, Luke Ong, Fabian Zaiser
2022 A* conf
Nonparametric Involutive Markov Chain Monte Carlo.
ICML
Carol Mak, Fabian Zaiser, Luke Ong
2022 J jnl
Nonparametric Involutive Markov Chain Monte Carlo.
CoRR
Carol Mak, Fabian Zaiser, Luke Ong
2022 A* conf
Probabilistic Verification Beyond Context-Freeness.
LICS
Guanyan Li, Andrzej S. Murawski, Luke Ong
2022 A* conf
Rethinking Variational Inference for Probabilistic Programs with Stochastic Support.
NeurIPS
Tim Reichelt, Luke Ong, Thomas Rainforth
2021 — conf
Abstract: The Extended Theory of Trees and Algebraic (Co)datatypes.
SMT
Fabian Zaiser, Luke Ong
2021 J jnl
Expectation Programming.
CoRR
Tim Reichelt, Adam Golinski, Luke Ong, Tom Rainforth
2021 A* conf
Initial Limit Datalog: a New Extensible Class of Decidable Constrained Horn Clauses.
LICS
Toby Cathcart Burn, Luke Ong, Steven J. Ramsay, Dominik Wagner
2021 J jnl
Initial Limit Datalog: a New Extensible Class of Decidable Constrained Horn Clauses.
CoRR
Toby Cathcart Burn, Luke Ong, Steven J. Ramsay, Dominik Wagner
2021 A* conf
Nonparametric Hamiltonian Monte Carlo.
ICML
Carol Mak, Fabian Zaiser, Luke Ong
2021 J jnl
Nonparametric Hamiltonian Monte Carlo.
CoRR
Carol Mak, Fabian Zaiser, Luke Ong
2021 J jnl
On Probabilistic Termination of Functional Programs with Continuous Distributions.
CoRR
Raven Beutner, Luke Ong
2021 A* conf
On probabilistic termination of functional programs with continuous distributions.
PLDI
Raven Beutner, Luke Ong
2021 J jnl
Supermartingales, Ranking Functions and Probabilistic Lambda Calculus.
CoRR
Andrew Kenyon-Roberts, Luke Ong
2020 J jnl
A Differential-form Pullback Programming Language for Higher-order Reverse-mode Automatic Differentiation.
CoRR
Carol Mak, Luke Ong
2018 J jnl
Simulating cardinal preferences in Boolean games: A proof technique.
Inf. Comput.
Egor Ianovski, Luke Ong
2018 J jnl
The complexity of decision problems about equilibria in two-player Boolean games.
Artif. Intell.
Egor Ianovski, Luke Ong
2017 A conf
Deciding Secrecy of Security Protocols for an Unbounded Number of Sessions: The Case of Depth-Bounded Processes.
CSF
Emanuele D'Osualdo, Luke Ong, Alwen Tiu
2017 C ed.
Formal Methods and Software Engineering - 19th International Conference on Formal Engineering Methods, ICFEM 2017, Xi'an, China, November 13-17, 2017, Proceedings
ICFEM
Zhenhua Duan, Luke Ong
2016 J jnl
Higher-Order Model Checking (NII Shonan Meeting 2016-4).
NII Shonan Meet. Rep.
Naoki Kobayashi, Luke Ong, Igor Walukiewicz
2016 J jnl
Information flow analysis for a dynamically typed language with staged metaprogramming.
J. Comput. Secur.
Martin Mariusz Lester, Luke Ong, Max Schäfer
2015 J jnl
A Type System for proving Depth Boundedness in the pi-calculus.
CoRR
Emanuele D'Osualdo, Luke Ong
2015 A* conf
Higher-Order Model Checking: An Overview.
LICS
Luke Ong
2014 J jnl
Detecting Redundant CSS Rules in HTML5 Applications: A Tree-Rewriting Approach.
CoRR
Matthew Hague, Anthony Widjaja Lin, Luke Ong
2014 A* conf
EGuaranteeNash for Boolean Games Is NEXP-Hard.
KR
Egor Ianovski, Luke Ong
2013 — ed.
Computation, Logic, Games, and Quantum Foundations. The Many Facets of Samson Abramsky - Essays Dedicated to Samson Abramsky on the Occasion of His 60th Birthday
Computation, Logic, Games, and Quantum Foundations
Bob Coecke, Luke Ong, Prakash Panangaden
2013 J jnl
EGuaranteeNash for Boolean Games is NEXP-Hard.
CoRR
Egor Ianovski, Luke Ong
2013 A conf
Information Flow Analysis for a Dynamically Typed Language with Staged Metaprogramming.
CSF
Martin Lester, Luke Ong, Max Schäfer
2013 C conf
Recursion Schemes, Collapsible Pushdown Automata and Higher-Order Model Checking.
LATA
Luke Ong
2012 — conf
Soter: an automatic safety verifier for erlang.
AGERE!@SPLASH
Emanuele D'Osualdo, Jonathan Kochems, Luke Ong
2011 J jnl
Automated Techniques for Higher-Order Program Verification (NII Shonan Meeting 2011-5).
NII Shonan Meet. Rep.
Naoki Kobayashi, Luke Ong, David Van Horn