Mikko Koivisto
27 papers · 2004–2025 · 8 conferences · across top CS/AI conferences
Achievements
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π§ Keyword Pioneer π£ Hot Topic Early Bird π Interdisciplinary Bridge πΊοΈ Taxonomy Completionist (14) π Conference Polyglot (8)
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Cross-Pollinator
(13)
π§
Keyword Pioneer
π£
Hot Topic Early Bird
π
Keyword Trendsetter Combo
(3)
π
Keyword Champion
(2)
π§¬
Topic Evolution
π
Century Club
(27)
π
Trend Setter
π
Conference Pioneer
π₯
Unstoppable
(13)
ποΈ
Keyword Collector
(84)
Conferences
UAI (6)
AAAI (4)
IJCAI (4)
NIPS (4)
AISTATS (3)
JMLR (3)
ICML (2)
PGM (1)
Top co-authors
Research topics
Keywords
bayesian network
(10)
structure learning
(8)
directed acyclic graph
(8)
markov chain monte carlo
(6)
graphical model
(6)
partial order
(4)
dynamic programming
(3)
combinatorial optimization
(3)
posterior probability
(3)
linear extension
(2)
importance sampling
(2)
bayesian inference
(2)
matrix permanent
(2)
exact inference
(2)
bayesian network structure learning
(2)
posterior distribution
(2)
causal discovery
(2)
causal effect
(2)
rejection sampling
(2)
graph sampling
(2)
Papers
Quantum Speedups for Bayesian Network Structure Learning
UAI 2025
Estimating the Permanent by Nesting Importance Sampling
ICML 2024
Faster Perfect Sampling of Bayesian Network Structures
UAI 2024
Revisiting Bayesian network learning with small vertex cover
UAI 2023
On inference and learning with probabilistic generating circuits
UAI 2023
A Faster Practical Approximation Scheme for the Permanent
AAAI 2023
Trustworthy Monte Carlo
NIPS 2022
Approximating the Permanent with Deep Rejection Sampling
NIPS 2021
Error-Correcting and Verifiable Parallel Inference in Graphical Models
AAAI 2020
Towards Scalable Bayesian Learning of Causal DAGs
NIPS 2020
Layering-MCMC for Structure Learning in Bayesian Networks
UAI 2020
A Bayesian Approach for Estimating Causal Effects from Observational Data
AAAI 2020
Exact Sampling of Directed Acyclic Graphs from Modular Distributions
UAI 2019
Counting and Sampling Markov Equivalent Directed Acyclic Graphs
AAAI 2019
On Structure Priors for Learning Bayesian Networks
AISTATS 2019
Intersection-Validation: A Method for Evaluating Structure Learning without Ground Truth
AISTATS 2018
A Scalable Scheme for Counting Linear Extensions
IJCAI 2018
Finding Optimal Bayesian Networks with Local Structure
PGM 2018
The Mixing of Markov Chains on Linear Extensions in Practice
IJCAI 2017
Counting Linear Extensions of Sparse Posets
IJCAI 2016
Structure Discovery in Bayesian Networks by Sampling Partial Orders
JMLR 2016
Dealing with small data: On the generalization of context trees
ICML 2015
Learning Chordal Markov Networks by Dynamic Programming
NIPS 2014
Finding Optimal Bayesian Networks Using Precedence Constraints
JMLR 2013
Annealed Importance Sampling for Structure Learning in Bayesian Networks
IJCAI 2013
Bayesian structure discovery in Bayesian networks with less space
AISTATS 2010
Exact Bayesian Structure Discovery in Bayesian Networks
JMLR 2004