Feb
20
2:00 PM14:00
Melih Kandemir: Embodied Estimators for Full Autonomy
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Mar
19
1:00 PM13:00
FCAI + FAME SIG: AI for Inverse Problems and Imaging Kickoff Event
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Feb
12
5:00 PM17:00
Encounters with the Machine: Humanity and AI (Hanaholmen 50)
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Feb
5
8:30 AM08:30
AIX Forum - Medical Device Regulation and AI: Success Stories
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Feb
4
12:30 PM12:30
Feb
3
5:00 PM17:00
Jan
15
1:00 PM13:00
Dec
19
2:00 PM14:00
Tor Fjelde: Turing.jl: a general-purpose probabilistic programming language
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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
3
9:00 AM09:00
Dec
2
5:00 PM17:00
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
28
2:30 PM14:30
Industry and Society Webinar: Empirical design of experiments with AI
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Nov
27
4:00 PM16:00
CRAI-CIS Seminar: The value of structural features for cross-language prominent content analysis
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Nov
21
2:00 PM14:00
Fabrizio Ventola: Robust probabilistic circuits for efficient and reliable predictions
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Nov
11
2:00 PM14:00
Andrew Cropper: The Automatic Computer Scientist
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Nov
7
4:00 PM16:00
Nikola Surjanovic: Software and MCMC methods for sampling from complex distributions
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Oct
28
5:00 PM17:00
Oct
24
2:00 PM14:00
Aliaksandra Shysheya: On Conditional Diffusion Models for PDE Simulations
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Oct
24
9:00 AM09:00
Oct
21
to Oct 22
Oct
10
2:00 PM14:00
Hannes Stark & Bowen Jing: Generative Models for Biomolecular Prediction, Dynamics, and Design
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Sep
30
1:00 PM13:00
Toni Karvonen: Probabilistic Richardson extrapolation
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Sep
26
2:30 PM14:30
Sep
26
2:00 PM14:00
Erik Englesson: Exploiting Properties of the Gaussian Likelihood for Label Noise Robustness in Classification
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Sep
23
5:00 PM17:00
Sep
12
2:00 PM14:00
Thomas Möllenhoff: Variational Learning is Effective for Large Deep Networks
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Jul
1
to Jul 5
ELLIS Summer School: Collaborative and Generative AI
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Jun
28
9:00 AM09:00
ELLIS Workshop on Probabilistic Numerics and Physics-Informed Learning
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Jun
27
to Jun 28
Jun
17
2:00 PM14:00
Maximilian Naegele: Tackling Decision Processes with Non-Cumulative Objectives using Reinforcement Learning
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