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Promovierendenkolloquium | Informatik und Data Science

KI&ML-Kolloquium

We will discuss State Space Models and Normalizing Flows based on the list of papers below.
 

Meeting Details:
When: Mondays 14:00 – 17:00
Where: Besprechungsraum inIT, CIIT building in Lemgo/Webex
What: Usually two talks per session

Please note that the seminar will primarily take place in person to encourage discussion, with a very limited Webex option for those unable to attend on site.

Contact: Prof. Dr. Marcus Lange-Hegermann (TH Ostwestfalen-Lippe)

 

State Space Models
1) HiPPO: Recurrent Memory with Optimal Polynomial Projections (https://arxiv.org/abs/2008.07669): Nico, 29.09.2025
2) Efficiently Modeling Long Sequences with Structured State Spaces (https://arxiv.org/abs/2111.00396): Ruwen, 29.09.2025
3) On the Parameterization and Initialization of Diagonal State Space Models (https://arxiv.org/abs/2206.11893): Andreas, 06.10.2025
4) Mamba: Linear-Time Sequence Modeling with Selective State Spaces (https://arxiv.org/abs/2312.00752): Thomas, 06.10.2025

Applications (optional):
1. Hyena Hierarchy: Towards Larger Convolutional Language Models (https://arxiv.org/abs/2302.10866)
2. It's Raw! Audio Generation with State-Space Models (https://arxiv.org/abs/2202.09729)
3. VMamba: Visual State Space Model (https://arxiv.org/abs/2401.10166)
4. MambaAD: Exploring State Space Models for Multi-class Unsupervised Anomaly Detection (https://arxiv.org/abs/2404.06564)

Normalizing Flows
1. Variational Inference with Normalizing Flows (https://arxiv.org/abs/1505.05770)
2. NICE: Non-linear Independent Components Estimation (https://arxiv.org/abs/1410.8516)
3. Density estimation using Real NVP (https://arxiv.org/abs/1605.08803)
4. Masked Autoregressive Flow for Density Estimation (https://arxiv.org/abs/1705.07057)
5. Glow: Generative Flow with Invertible 1x1 Convolutions (https://arxiv.org/abs/1807.03039)
6. FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models (https://arxiv.org/abs/1810.01367)
7. Flow Matching for Generative Modeling (https://arxiv.org/abs/2210.02747)
8. Transforming Gaussian Processes With Normalizing Flows (https://arxiv.org/abs/2011.01596) (optional)


Linda Rustemeier, M.A.

Coordination of the Department of Computer and Data Science

Do you have any questions about the Department or need further information? Please contact us.

Department of Computer and Data Science

Do you have any questions about the Department or need further information? Please contact us.