Juha Harviainen

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I’m a doctoral student at the University of Helsinki working in the Sums of Products research group under the supervision of professor Mikko Koivisto. My research focuses currently on perfect sampling and #P-complete problems, and I’m interested in randomized algorithms, complexity theory and information theory more generally.


  • Revisiting Bayesian Network Learning with Small Vertex Cover. Juha Harviainen, Mikko Koivisto. UAI 2023 (to appear).
  • On Inference and Learning With Probabilistic Generating Circuits. Juha Harviainen, Vaidyanathan Peruvemba Ramaswamy, Mikko Koivisto. UAI 2023 (to appear).
  • A Faster Practical Approximation Scheme for the Permanent. Juha Harviainen, Mikko Koivisto. AAAI 2023 (to appear).
  • Trustworthy Monte Carlo. Juha Harviainen, Mikko Koivisto, Petteri Kaski. NeurIPS 2022.
  • Approximating the Permanent with Deep Rejection Sampling. Juha Harviainen, Antti Röyskö, Mikko Koivisto. NeurIPS 2021.
  • 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. ISSRE Workshops 2019.


  • Tie koodariksi. A website for Finnish schools for teaching programming made by me, Antti Laaksonen, Roope Salmi and Topi Talvitie.


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