The Hungarian Machine Learning Days provide an opportunity for Hungarian machine learning researchers working in foreign institutions to meet each other and connect with those working in Hungary, including the younger generation and Ph.D. students.
During the 3-day informal summer event, internationally recognized researchers will present tutorials, young researchers will give short presentations, posters, and ideas, and there will be many informal joint programs.
Participation, lunch, and coffee breaks are free of charge but require registration.
All presentations are in English. For posters, please apply during registration in time. Late poster applications risk no space remaining available.
9:00 Arrival, coffee
Regular talks
9:30 András Kemler (Bosch): Welcome
9:45 Dániel Baráth (ETH Zürich): Cross-Modal Localization
10:15 András György (Deepmind)
10:45 Fanghui Liu (Shanghai Jiao Tong University): From SLT4AI to AI4SLT: Generalization under scaling, and formalized empirical processes in Lean 4 (infrastructure)
11:15 Róbert Busa-Fekete (Google Research): Filtering: Sample-Efficient Tree-Based Data Filtering
11:45 Miranda Christ (UC Berkeley)
Lunch
14:00 Poster Booster
16:00 Coffee and Poster session
9:00 Arrival, coffee
Regular talks
9:30 Péter Horváth (State Secretary for Research and Szeged Biological Research): Welcome and Hungarian AI Strategy
9:45 Gergely Flamich (Imperial College London): Data Compression with Diffusion Models
10:15 Spencer Hill (Queen's University): Rejection Sampling is Optimal for Relative Entropy Coding
10:45 Noémi Éltető (MPI Tübingen, DeepMind): ATLAS: Active Theory Learning for Automated Science
11:15 Dániel Barabási (FutureHouse San Francisco): Building an AI Scientist: Applications to Neuroscience
11:45 Tamás Stenczel (Cambridge)
Lunch
14:00 Péter Horváth (state Secretary for Research and Szeged Biological Research): Machine vision in microbiology (TBC)
14:30 Szilvia Újváry (Cambridge)
15:00 Balázs Meszéna (Wigner): TAVAE: A VAE with Adaptable Priors Explains Contextual Modulation in the Visual Cortex
15:30 Ambrus Tamás (SZTAKI): On Rate-Optimal Partitioning Classification from Observable and from Privatised Data
16:00 Roundtable: Role and Boundaries of LLMs in scientific work
16:30 Coffee and Poster session
9:00 Arrival, coffee
Regular talks
10:00 Gergely Neu (UPF Barcelona): Generative modeling by value-driven transport
10:30 Csaba Beleznai (Austrian Institute of Technology): 3D spatial perception and object manipulation
11:00 Ádám Zsolt Wagner (DeepMind)
11:30 Mihály Petreczky (CNRS Lille):
12:00 Anna Kerekes (Cambridge)
Lunch
Short/Student talks
14:00 Domokos Kelen (Mastercard): Regression Uncertainty in Neural Networks
14:30 András Balogh (Szeged): Verification of the Implicit World Model in a Generative Model via Adversarial Sequences
15:00 Dániel Rácz (SZTAKI)
15:30 Gergely Csáji (Eötvös University Budapest), Clustering via Hedonic Games: New Concepts and Algorithms
16:00 Roundtable: AI "consciousness"?
16:30 Coffee and Poster session
Registration: personalized invitation is sent to those on MILAB events list
Our location is Bosch Budapest Innovation Campus (Campus II),
Budapest, Robert Bosch utca 14, 1103
- right at the Kőbánya-Kispest Metro terminal.
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