30.04.2024

MCML at ICLR 2024

The 12th International Conference on Learning Representations (ICLR 2024). Vienna, Austria, May 07-11, 2024

We are happy to announce that MCML researchers are represented with 22 papers at ICLR 2024:

K. Ahn, X. Cheng, M. Song, C. Yun, A. Jadbabaie and S. Sra.
Linear attention is (maybe) all you need (to understand Transformer optimization).
URL.

S. Chen, Z. Han, B. He, M. Buckley, P. Torr, V. Tresp and J. Gu.
Understanding and Improving In-Context Learning on Vision-language Models. (Workshop paper).
URL.

S. Chen, Z. Han, B. He, Z. Ding, W. Yu, P. Torr, V. Tresp and J. Gu.
Red Teaming GPT-4V: Are GPT-4V Safe Against Uni/Multi-Modal Jailbreak Attacks?. (Workshop paper).
URL.

S. d'Ascoli, S. Becker, P. Schwaller, A. Mathis and N. Kilbertus.
ODEFormer: Symbolic Regression of Dynamical Systems with Transformers.
URL. GitHub.

L. Eyring, D. Klein, T. Uscidda, G. Palla, N. Kilbertus, Z. Akata and F. J. Theis.
Unbalancedness in Neural Monge Maps Improves Unpaired Domain Translation.
URL.

D. Frauen, F. Imrie, A. Curth, V. Melnychuk, S. Feuerriegel and M. van der Schaar.
A Neural Framework for Generalized Causal Sensitivity Analysis.
URL.

S. Gupta, S. Jegelka, D. Lopez-Paz and K. Ahuja.
Context is Environment.
URL. GitHub.

S. Gupta, J. Robinson, D. Lim, S. Villar and S. Jegelka.
Structuring Representation Geometry with Rotationally Equivariant Contrastive Learning.
URL. GitHub.

K. Hess, V. Melnychuk, D. Frauen and S. Feuerriegel.
Bayesian neural controlled differential equations for treatment effect estimation.
URL.

Y. Huang, W. Lu, J. Robinson, Y. Yang, M. Zhang, S. Jegelka and P. Li.
On the Stability of Expressive Positional Encodings for Graphs.
URL. GitHub.

B. Kiani, T. Le, H. Lawrence, S. Jegelka and M. Weber.
On the hardness of learning under symmetries.
URL.

R. Kohli, M. Feurer, B. Bischl, K. Eggensperger and F. Hutter.
Towards Quantifying the Effect of Datasets for Benchmarking: A Look at Tabular Machine Learning. (Workshop paper).
URL.

C. Koke and D. Cremers.
HoloNets: Spectral Convolutions do extend to Directed Graphs.
URL.

T. Le, L. Ruiz and S. Jegelka.
A Poincaré Inequality and Consistency Results for Signal Sampling on Large Graphs.
URL.

M. Lienen, D. Lüdke, J. Hansen-Palmus and S. Günnemann.
From Zero to Turbulence: Generative Modeling for 3D Flow Simulation.
URL.

V. Melnychuk, D. Frauen and S. Feuerriegel.
Bounds on Representation-Induced Confounding Bias for Treatment Effect Estimation.
URL.

A. Palma, T. Richter, H. Zhang, A. Dittadi and F. J. Theis.
cellFlow: a generative flow-based model for single-cell count data. (Workshop paper).
URL.

P. Schnell and N. Thuerey.
Stabilizing Backpropagation Through Time to Learn Complex Physics.
URL. GitHub.

M. Schröder, D. Frauen and S. Feuerriegel.
Causal Fairness under Unobserved Confounding: A Neural Sensitivity Framework.
URL.

S. Solonets, D. Sinitsyn, L. Von Stumberg, N. Araslanov and D. Cremers.
An Analytical Solution to Gauss-Newton Loss for Direct Image Alignment.
URL.

A. Vahidi, S. Schoßer, L. Wimmer, Y. Li, B. Bischl, E. Hüllermeier and M. Rezaei.
Probabilistic Self-supervised Learning via Scoring Rules Minimization.
URL. GitHub.

R. Winchenbach and N. Thuerey.
Symmetric Basis Convolutions for Learning Lagrangian Fluid Mechanics.
URL. GitHub.

30.04.2024

Link to MCML PI Alexander Fraser receives EU funding for research on LLMs

©LMU/TUM

16.10.2024

MCML PI Alexander Fraser receives EU funding for research on LLMs

Our PI Alexander Fraser is leading a new EU-funded research initiative focused on advancing large language models (LLMs) and their societal impacts.

10.09.2024

MCML at ECML-PKDD 2024

We are happy to announce that MCML researchers are represented at ECML-PKDD 2024.

14.08.2024

MCML at ACL 2024

We are happy to announce that MCML researchers are represented at the 62nd Annual Meeting of the Association for Computational Linguistics (ACL 2024).

20.07.2024

MCML at ICML 2024

We are happy to announce that MCML researchers are represented at the 41st International Conference on Machine Learning (ICML 2024).

15.07.2024

MCML at UAI 2024

We are happy to announce that MCML researchers are represented at the 40th Conference on Uncertainty in Artificial Intelligence (UAI 2024).

MCML at ICLR 2024

The 12th International Conference on Learning Representations (ICLR 2024). Vienna, Austria, May 07-11, 2024

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