Apr
14
2:00 PM14:00
Ossi Räisä: Noise-Aware Differentially Private Regression via Meta-Learning
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May
8
2:00 PM14:00
François-Xavier Briol: Robust and Conjugate Gaussian Processes Regression
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May
26
2:00 PM14:00
Feb
20
2:00 PM14:00
Melih Kandemir: Embodied Estimators for Full Autonomy
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Dec
9
2:00 PM14:00
Linda Mannila: AI in the classroom – designing AI literacy for K-12 education
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Dec
2
2:00 PM14:00
Antti Oulasvirta: Better AI with Better Human Models
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Nov
29
9:30 AM09:30
Grigorios Tsoumakas: Neural Abstractive Summarization
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Nov
11
2:00 PM14:00
Andrew Cropper: The Automatic Computer Scientist
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Sep
30
1:00 PM13:00
Toni Karvonen: Probabilistic Richardson extrapolation
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Jun
17
2:00 PM14:00
Maximilian Naegele: Tackling Decision Processes with Non-Cumulative Objectives using Reinforcement Learning
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Jun
10
2:00 PM14:00
Mine Dogucu: Updating Beliefs on Bayesian Education: Reflections on Research and Teaching Projects
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May
20
2:00 PM14:00
Mikko Koivisto: Bayesian inference of causal graphs: where we are and where we should go
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May
6
2:15 PM14:15
Matias Turkulainen: NeRFs and 3D Gaussian Splatting: Survey and Applications in 3D Computer Vision
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Apr
22
2:00 PM14:00
Michael Mathioudakis: Algorithms for Efficient Machine Learning (ML)
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Apr
8
2:15 PM14:15
Mikko Mäkelä: Bayesian optimization for design of experiments
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Mar
28
10:15 AM10:15
David Leslie: Reinforcement learning in bandits and games
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Mar
25
2:00 PM14:00
Chen He: VMS: Interactive Visualization to Support the Sensemaking and Selection of Predictive Models
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Mar
11
2:00 PM14:00
Mashrura Musharraf: Navigating Tomorrow: Putting People at the Helm of Maritime Digitalization and Automation
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Feb
26
2:00 PM14:00
Daniel Schmidt: Fast and Accurate Probabilistic Time Series Classification
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Feb
12
2:15 PM14:15
Martin Trapp: Flexible and Efficient Probabilistic Modeling with Tractable Circuits
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Jan
29
2:00 PM14:00
Ayush Bharti: Robust and sample-efficient simulation-based inference
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Dec
14
2:00 PM14:00
Carl Henrik Ek: Modulated Surrogates for Bayesian Optimisation
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Nov
27
2:00 PM14:00
Jörg Tiedemann: Releasing the MAMMOTH - a framework for large-scale modular multilingual NLP models
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Nov
2
2:00 PM14:00
Justin Domke: Monte Carlo Variational Inference
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Oct
30
2:00 PM14:00
Aaro Järvinen: The role of machine learning in facilitating fusion energy research
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Oct
16
2:00 PM14:00
Bo Zhao: Scalable and Flexible Distributed Reinforcement Learning Systems
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Oct
2
2:00 PM14:00
May
29
2:15 PM14:15
Alex Jung: A Total Variation Minimization Perspective on Trustworthy Federated Learning
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May
15
2:15 PM14:15
Julien Martinelli: Multi-Fidelity Bayesian Optimization with Unreliable Information Sources
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May
9
2:00 PM14:00
Ossi Räisä: Noise-Aware Statistical Inference with Differentially Private Synthetic Data
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Apr
24
2:00 PM14:00
Apr
17
2:15 PM14:15
Past three years of NVIDIA AI Technology Center Finland and the journey ahead
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Apr
3
2:00 PM14:00
Maria Brbic: Machine Learning for Biomedical Discovery
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