Seminar | TransferLab — appliedAI Institute

Seminar

The TransferLab Seminar is a platform where researchers and engineers share and discuss recent advances in AI/ML, striking a balance between accessibility and mathematical depth.

We organize comprehensive talks on ML, RL, DL and statistics, emphasizing both theoretical understanding and practical implementation. These range from introductory overviews to recent developments - and are open to all interested individuals!

Each talk, lasting about 45min followed by around 15min discussion, focuses on a specific topic related to our ongoing series topics. To stay informed, follow the appliedAI Institute on LinkedIn. If you’re interested in presenting your work, contact us.

Upcoming Talks

RAGAR, Your Falsehood RADAR: RAG-Augmented Reasoning for Political Fact-Checking using Multimodal Large Language Models - Mohammed Abdul Khaliq (University of Stuttgart)

Apr 18, 2024

Mohammed Abdul Khaliq, MSc. Computational Linguistics Programm at the Institute for Natural Language Processing of the University of Stuttgart, will give a talk on the topic of his Master’s thesis: “RAGAR, Your Falsehood RADAR: RAG-Augmented Reasoning for Political Fact-Checking using Multimodal Large Language Models”.

Large Language Models

Mohammed Abdul Khaliq

LAVA: Data Valuation Without Pre-Specified Learning Algorithms - Feiyang Kang (Virginia Tech)

May 2, 2024

Today’s talk is about LAVA, an Optimal-Transport-based approach to data valuation that dispenses with training of a model to compute values.

Previous Talks

Second-Order Information and Applications - Kristof Schröder (appliedAI Institute)

Apr 11, 2024

Kristof Schröder will talk about second-order information and its applications in machine learning.

Optimization in ML

Kristof Schröder

Predictive, Scalable and Interpretable Knowledge Tracing on Structured Domains - Álvaro Tejero-Cantero (University of Tübingen)

Apr 4, 2024

Álvaro Tejero-Cantero, group leader at the ml ⇌ science colab (University of Tübingen), will present PSI-KT, a hierarchical generative approach for estimating a learner’s progress, spotlight at ICLR 2024.

Probabilistic Models

Álvaro Tejero-Cantero

Conditional Flow Matching: Simulation-Free Dynamic Optimal Transport - Alex Tong (MILA)

Mar 21, 2024

Alex Tong, postdoctoral fellow at MILA (Université de Montréal), will talk about conditional flow matching, a family of simulation-free training objectives for continuous normalizing flows.

Probabilistic Models

Mind the Gap: Methods and Applicability of Simulation-Based Inference - Jan Teusen (appliedAI Institute)

Mar 14, 2024

Jan Teusen (né Boelts), AI Researcher at appliedAI Institute, will give a gentle introduction to simulation-based inference (SBI), along with a presentation of his own research on new SBI methods for computational neuroscience and new software tools.

Simulation-Based Inference

Studying LLMs with Influence Functions - Fabio Peruzzo (appliedAI Initiative)

Feb 29, 2024

Fabio Peruzzo, Senior AI Engineer at appliedAI Initiative, will talk about a recent work on the use of influence functions to study the behavior of LLMs.

Representation Equivalent Neural Operators - Emmanuel de Bézenac (ETH)

Feb 22, 2024

Emmanuel de Bézenac, Postdoctoral Research Fellow at ETH Zurich, will talk about discretization in neural operators, the novel framework of Representation equivalent Neural Operators, as well as Convolutional Neural Operators.

Simulation and AI

Emmanuel de Bézenac

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Our Block Seminars

Methods and issues in Explainable AI

This seminar series explores the landscape of Explainable Artificial Intelligence (XAI) beyond the content in our training on XAI, and through a comprehensive selection of papers in the field. By the end of this series, participants will …

May 17, 2023

Uncertainty quantification for neural networks

In this seminar series, we review seminal and recent papers on uncertainty quantification that didn’t make it into our training on Bayesian ML.

Oct 22, 2022