Guy Van den Broeck
where else to find them
what they talk about
where they keep going back
- OOPSLA2 editions2020–2025
all 6 in the filters
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all 6 in the filters
who talks about the same things
- Todd Millstein11 talks
- Poorva Garg3 talks
- Steven Holtzen12 talks
- Harrison Goldstein10 talks
- Benjamin C. Pierce17 talks
- Vikash K. Mansinghka24 talks
| title | conference | date |
|---|---|---|
| Tuning Random Generators: Property-Based Testing as Probabilistic Programming | OOPSLA 2025 | 2025-10-16 |
Generators become probabilistic programs with symbolic weights and are tuned by computing a symbolic distribution, compiling it into compressed BDD-based… | ||
| Bit Blasting Probabilistic Programs | PLDI 2024 | 2024-06-24 |
Presents a new discretization called bit blasting that encodes continuous variables as Boolean bits so a domain of 2^b points becomes a discrete program over… | ||
| Logic and Probabilistic Circuits 1 | Logic and Algorithms in Database Theory and AI Boot Camp | 2023-08-21 |
Main claim: represent probability models as layered computation graphs so many queries become provably efficient when the circuit enforces decomposability… | ||
| Logic and Probabilistic Circuits 4 | Logic and Algorithms in Database Theory and AI Boot Camp | 2023-08-21 |
Computing a log of a probabilistic circuit requires log requires determinism because otherwise output loses determinism and the problem becomes NP‑hard; the… | ||
| Bit-Blasting Probabilistic Programs | LAFI 2023 | 2023-01-15 |
HyBit converts continuous variables into a discrete bitblasted representation by encoding each real as independent Bernoulli bits, then runs exact inference… | ||
| Tractable Probabilistic Circuits | Algorithmic Aspects of Causal Inference 2022 | 2022-03-18 |
Introduces tractable probabilistic circuits as sum‑product DAGs learned via Chow‑Liu → hidden tree → circuit and trained with mini‑batch EM on GPUs; achieves… | ||
| Scaling Exact Inference for Discrete Probabilistic Programs | OOPSLA 2020 | 2020-11-15 |
Introduces Dice as a discrete PPL that compiles programs to binary decision diagrams and performs inference by weighted model counting, reusing compiled… | ||
| Probabilistic Reasoning by First-Order Model Counting | Uncertainty in Computation 2016 | 2016-10-04 |
Weighted first‑order model counting (WFOMC) reduces Markov logic networks to a sentence plus a weight function and exploits weight symmetry to perform lifted… | ||
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