13
Feb

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AI Keynote Series • 13.02.2025 • Online via Zoom
10:00 am - 11:30 am
Simplifying Debiased Inference via Automatic Differentiation and Probabilistic Programming
Alex Luedtke, Department of Statistics, University of Washington
The speaker would introduce an algorithm that simplifies the construction of efficient estimators, making them accessible to a broader audience. ‘Dimple’ takes as input computer code representing a parameter of interest and outputs an efficient estimator. Unlike standard approaches, it does not require users to derive a functional derivative known …
13
Feb

Virtual Workshop on Generative AI with Diffusion Models • 13.02.2025 • Virtual
9:00 am - 5:00 pm
Generative AI With Diffusion Models
Virtual Workshop From Nvidia
Generative AI plays a significant role across industries. In this course, learners will take a deeper dive into denoising diffusion models.
12
Feb

Virtual Workshop on Data Science with RAPIDS • 12.02.2025 • Virtual
9:00 am - 5:00 pm
Fundamentals of Accelerated Data Science With RAPIDS
Virtual Workshop From Nvidia
In this workshop, you’ll learn how to build and execute end-to-end GPU-accelerated data science workflows. Using the RAPIDS™-accelerated data science libraries, you’ll apply a wide variety of GPU-accelerated machine learning algorithms for data analysis.
06
Feb

MCML Stammtisch • 06.02.2025 • Gasthaus FUX, Türkenstraße 38, 80799 München
6:00 pm - 8:00 pm
MCML Stammtisch - February Edition
Join Us for an Evening of Connection and Conversation
We heartily invite to the next MCML-Stammtisch edition, taking place on Thursday, February 6th, at 6 pm, at Gasthaus FUX, Türkenstraße 38, Munich (very close to “U3 Universität”). Happy to see you there.
06
Feb

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Lecture • 06.02.2025 • LMU Munich, Ludwigstr. 28 VG/II; Room 211b
11:00 am - 12:00 pm
Causal Discovery: What Can We Learn From Heterogeneous Noise?
Alexander Marx, TU Dortmund
Causal discovery aims to learn causal networks, i.e., directed acyclic graphs (DAGs), from observational data. Although the problem is not feasible in the most general form, as it is not possible to infer causal relations from pure correlations, we can define structural assumptions about the functional relations underlying our observed system to …
06
Feb
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07
Feb

Conference • 06.02.2025 - 07.02.2025 • Institut Polytechnique de Paris, École Polytechnique Campus, Route de Saclay, 91120 Palaiseau, France
9:30 am - 5:30 pm
AI, Science, and Society Conference
Daniel Cremers, MCML
We are pleased to announce that Daniel Cremers, Director of the MCML, will be a featured speaker at the upcoming conference titled “AI, Science, and Society: Connections, Collectives, and Collaboration.” This interdisciplinary event is scheduled to take place on February 6 and 7, 2025, at the Institut Polytechnique de Paris.