Research output per year
Research output per year
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Dive into the research topics where David Tolpin is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
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Collaborations and top research areas from the last five years
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Probabilistic Programs as an Action Description Language
Brafman, R. I., Tolpin, D. & Wertheim, O., 27 Jun 2023, AAAI-23 Special Programs, IAAI-23, EAAI-23, Student Papers and Demonstrations. Williams, B., Chen, Y. & Neville, J. (eds.). AAAI press, p. 15351-15358 8 p. (Proceedings of the 37th AAAI Conference on Artificial Intelligence, AAAI 2023; vol. 37).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
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Monitoring Time Series with Missing Values: A Deep Probabilistic Approach
Barazani, O. & Tolpin, D., 1 Jan 2022, Cyber Security, Cryptology, and Machine Learning - 6th International Symposium, CSCML 2022, Proceedings. Dolev, S., Meisels, A. & Katz, J. (eds.). Springer Science and Business Media Deutschland GmbH, p. 19-28 10 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 13301 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
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Bob and Alice Go to a Bar: Reasoning About Future With Probabilistic Programs
Tolpin, D. & Dobkin, T., 6 Oct 2021.Research output: Working paper/Preprint › Preprint
Open Access -
How To Train Your Program: A Probabilistic Programming Pattern for Bayesian Learning From Data
Tolpin, D., 8 May 2021.Research output: Working paper/Preprint › Preprint
Open Access26 Downloads (Pure) -
Probabilistic Programs with Stochastic Conditioning
Tolpin, D., Zhou, Y., Rainforth, T. & Yang, H., 1 Jan 2021, Proceedings of the 38th International Conference on Machine Learning, ICML 2021. ML Research Press, p. 10312-10323 12 p. (Proceedings of Machine Learning Research; vol. 139).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
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Warped Input Gaussian Processes for Time Series Forecasting
Vinokur, I. & Tolpin, D., 1 Jan 2021, Cyber Security Cryptography and Machine Learning - 5th International Symposium, CSCML 2021, Proceedings. Dolev, S., Margalit, O., Pinkas, B. & Schwarzmann, A. (eds.). Springer Science and Business Media Deutschland GmbH, p. 205-220 16 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 12716 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
1 Scopus citations -
Bayesian Policy Search for Stochastic Domains
Tolpin, D., Zhou, Y. & Yang, H., 1 Oct 2020.Research output: Working paper/Preprint › Preprint
Open Access -
Stochastically Differentiable Probabilistic Programs
Tolpin, D., Zhou, Y. & Yang, H., 5 May 2020.Research output: Working paper/Preprint › Preprint
Open Access -
Stochastic Probabilistic Programs
Tolpin, D. & Dobkin, T., 2020.Research output: Working paper/Preprint › Preprint
Open Access -
ADVANCED COMPUTER SYSTEM DRIFT DETECTION
Lahav, O. M., Johnson, R. C. & Tolpin, D., 28 Mar 2019, IPC No. G06F 11/ 34 A I, Patent No. US2019095263, Priority date 28 Sep 2017, Priority No. US201715719279Research output: Patent
Thesis
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Rational Metareasoning in Problem-Solving Search
Author: Tolpin, D., 2014Supervisor: Shimony, E. S. (Supervisor)
Student thesis: Doctoral Thesis