Semi-Myopic Sensing Plans for Value Optimization - David Tolpin; Solomon Eyal Shimony (CoRR, 2009)

Rational Deployment of CSP Heuristics. - David Tolpin; Solomon Eyal Shimony (IJCAI, 2011)

MCTS Based on Simple Regret. - David Tolpin; Solomon Eyal Shimony (AAAI, 2012)

VOI-aware MCTS. - David Tolpin; Solomon Eyal Shimony (ECAI, 2012)

MCTS Based on Simple Rerget. - David Tolpin; Solomon Eyal Shimony (SOCS, 2012)

Selecting Computations: Theory and Applications. - Nicholas Hay; Stuart Russell 001; David Tolpin; Solomon Eyal Shimony (UAI, 2012)

Rational value of information estimation for measurement selection. - David Tolpin; Solomon Eyal Shimony (Intell. Decis. Technol., 2012)

Semimyopic Measurement Selection for Optimization Under Uncertainty. - David Tolpin; Solomon Eyal Shimony (IEEE Trans. Syst. Man Cybern. Part B, 2012)

Toward Rational Deployment of Multiple Heuristics in A. - David Tolpin; Tal Beja; Solomon Eyal Shimony; Ariel Felner; Erez Karpas (IJCAI, 2013)

Towards Rational Deployment of Multiple Heuristics in A* (Extended Abstract). - David Tolpin; Tal Beja; Solomon Eyal Shimony; Ariel Felner; Erez Karpas (SOCS, 2013)

Towards Rational Deployment of Multiple Heuristics in A* - David Tolpin; Tal Beja; Solomon Eyal Shimony; Ariel Felner; Erez Karpas (CoRR, 2013)

Rational Deployment of Multiple Heuristics in IDA. - David Tolpin; Oded Betzalel; Ariel Felner; Solomon Eyal Shimony (ECAI, 2014)

Justifying and Improving Meta-Agent Conflict-Based Search. - David Tolpin (CoRR, 2014)

ICBS: Improved Conflict-Based Search Algorithm for Multi-Agent Pathfinding. - Eli Boyarski; Ariel Felner; Roni Stern; Guni Sharon; David Tolpin; Oded Betzalel; Solomon Eyal Shimony (IJCAI, 2015)

Output-Sensitive Adaptive Metropolis-Hastings for Probabilistic Programs. - David Tolpin; Jan-Willem van de Meent; Brooks Paige; Frank D. Wood (ECML/PKDD (2), 2015)

Probabilistic Programming in Anglican. - David Tolpin; Jan-Willem van de Meent; Frank D. Wood (ECML/PKDD (3), 2015)

Maximum a Posteriori Estimation by Search in Probabilistic Programs. - David Tolpin; Frank D. Wood (SOCS, 2015)

Adaptive Scheduling in MCMC and Probabilistic Programming. - David Tolpin; Jan-Willem van de Meent; Brooks Paige; Frank D. Wood (CoRR, 2015)

Path Finding under Uncertainty through Probabilistic Inference. - David Tolpin; Brooks Paige; Frank D. Wood (CoRR, 2015)

Black-Box Policy Search with Probabilistic Programs. - Jan-Willem van de Meent; Brooks Paige; David Tolpin; Frank D. Wood (AISTATS, 2016)

Design and Implementation of Probabilistic Programming Language Anglican. - David Tolpin; Jan-Willem van de Meent; Hongseok Yang; Frank D. Wood (IFL, 2016)

Progressive Temporal Window Widening. - David Tolpin (CoRR, 2016)

Process monitoring on sequences of system call count vectors. - Michael Dymshits; Benjamin Myara; David Tolpin (ICCST, 2017)

Session Analysis using Plan Recognition. - Reuth Mirsky; Ya'akov Gal; David Tolpin (CoRR, 2017)

A Planning Approach to Monitoring Behavior of Computer Programs. - Alexandre Cukier; Ronen I. Brafman; Yotam Perkal; David Tolpin (CoRR, 2017)

A Planning Approach to Monitoring Computer Programs' Behavior. - Alexandre Cukier; Ronen I. Brafman; Yotam Perkal; David Tolpin (CSCML, 2018)

Rational deployment of multiple heuristics in optimal state-space search. - Erez Karpas; Oded Betzalel; Solomon Eyal Shimony; David Tolpin; Ariel Felner (Artif. Intell., 2018)

Deployable probabilistic programming. - David Tolpin (Onward!, 2019)

Population anomaly detection through deep gaussianization. - David Tolpin (SAC, 2019)

Warped Input Gaussian Processes for Time Series Forecasting. - David Tolpin (CoRR, 2019)

Stochastic Probabilistic Programs. - David Tolpin; Tomer Dobkin (CoRR, 2020)

Stochastically Differentiable Probabilistic Programs. - David Tolpin; Yuan Zhou 013; Hongseok Yang (CoRR, 2020)

Probabilistic Programs with Stochastic Conditioning. - David Tolpin; Yuan Zhou 013; Hongseok Yang (CoRR, 2020)

Bayesian Policy Search for Stochastic Domains. - David Tolpin; Yuan Zhou 013; Hongseok Yang (CoRR, 2020)

Warped Input Gaussian Processes for Time Series Forecasting. - Igor Vinokur; David Tolpin (CSCML, 2021)

Probabilistic Programs with Stochastic Conditioning. - David Tolpin; Yuan Zhou 013; Tom Rainforth; Hongseok Yang (ICML, 2021)

How To Train Your Program. - David Tolpin (CoRR, 2021)

Bob and Alice Go to a Bar: Reasoning About Future With Probabilistic Programs. - David Tolpin; Tomer Dobkin (CoRR, 2021)

Monitoring Time Series with Missing Values: A Deep Probabilistic Approach. - Oshri Barazani; David Tolpin (CSCML, 2022)

Probabilistic Programs as an Action Description Language. - Ronen I. Brafman; David Tolpin; Or Wertheim (AAAI, 2023)

Efficient Incremental Belief Updates Using Weighted Virtual Observations. - David Tolpin (CoRR, 2024)

Fast Neural Inverse Kinematics on Human Body Motions. - David Tolpin; Sefy Kagarlitsky (CoRR, 2025)

Neural Human Pose Prior. - Michal Heker; Sefy Kagarlitsky; David Tolpin (CoRR, 2025)