Juha Harviainen

According to our database, Juha Harviainen authored at least 20 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

The Power of Graph Doubling: Computing Ultrabubbles in a Bidirected Graph by Reducing to Weak Superbubbles.

Sebastian Schmidt, Juha Harviainen, Corentin Moumard, Aleksandr Politov, Francisco Sena, Alexandru I. Tomescu

CoRR, May, 2026

Exact and Approximate Algorithms for Polytree Learning.

Juha Harviainen, Frank Sommer, Manuel Sorge

CoRR, May, 2026

Identifying bubble-like subgraphs in linear-time via a unified SPQR-tree framework.

Francisco Sena, Aleksandr Politov, Corentin Moumard, Massimo Cairo, Romeo Rizzi, Manuel Cáceres, Sebastian Schmidt, Juha Harviainen, Alexandru I. Tomescu

CoRR, April, 2026

Learning Bayesian and Markov Networks with an Unreliable Oracle.

Juha Harviainen, Pekka Parviainen, Vidya Sagar Sharma

CoRR, March, 2026

2025

Identifying all snarls and superbubbles in linear-time, via a unified SPQR-tree framework.

Francisco Sena, Aleksandr Politov, Corentin Moumard, Manuel Cáceres, Sebastian Schmidt, Juha Harviainen, Alexandru I. Tomescu

CoRR, November, 2025

Scaling Up Bayesian DAG Sampling.

Daniele Nikzad, Alexander Zhilkin, Juha Harviainen, Jack Kuipers, Giusi Moffa, Mikko Koivisto

CoRR, October, 2025

Graph Reconstruction with a Connected Components Oracle.

Juha Harviainen, Pekka Parviainen

CoRR, September, 2025

Quantum Speedups for Bayesian Network Structure Learning.

Juha Harviainen, Kseniya Rychkova, Mikko Koivisto

Proceedings of the Conference on Uncertainty in Artificial Intelligence, 2025

Improving Decision Trees through the Lens of Parameterized Local Search.

Juha Harviainen, Frank Sommer, Manuel Sorge

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Optimal Decision Tree Pruning Revisited: Algorithms and Complexity.

Juha Harviainen, Frank Sommer, Manuel Sorge, Stefan Szeider

Proceedings of the Forty-second International Conference on Machine Learning, 2025

On Tractability of Learning Bayesian Networks with Ancestral Constraints.

Juha Harviainen, Pekka Parviainen

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2025

2024

Advances in Sampling and Counting Bipartite Matchings and Directed Acyclic Graphs.

Juha Harviainen

PhD thesis, 2024

Faster Perfect Sampling of Bayesian Network Structures.

Juha Harviainen, Mikko Koivisto

Proceedings of the Uncertainty in Artificial Intelligence, 2024

Estimating the Permanent by Nesting Importance Sampling.

Juha Harviainen, Mikko Koivisto

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

On inference and learning with probabilistic generating circuits.

Juha Harviainen, Vaidyanathan Peruvemba Ramaswamy, Mikko Koivisto

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Revisiting Bayesian network learning with small vertex cover.

Juha Harviainen, Mikko Koivisto

Proceedings of the Uncertainty in Artificial Intelligence, 2023

A Faster Practical Approximation Scheme for the Permanent.

Juha Harviainen, Mikko Koivisto

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Trustworthy Monte Carlo.

Juha Harviainen, Mikko Koivisto, Petteri Kaski

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Approximating the Permanent with Deep Rejection Sampling.

Juha Harviainen, Antti Röyskö, Mikko Koivisto

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2019

Software Framework for Data Fault Injection to Test Machine Learning Systems.

Jukka K. Nurminen, Tuomas Halvari, Juha Harviainen, Juha Mylläri, Antti Röyskö, Juuso Silvennoinen, Tommi Mikkonen

Proceedings of the IEEE International Symposium on Software Reliability Engineering Workshops, 2019