Martin Mundt

Martin Mundt

Goethe-Universität Frankfurt am Main

H-index: 12

Europe-Germany

About Martin Mundt

Martin Mundt, With an exceptional h-index of 12 and a recent h-index of 11 (since 2020), a distinguished researcher at Goethe-Universität Frankfurt am Main, specializes in the field of neural networks, deep learning, continual learning, computer vision.

His recent articles reflect a diverse array of research interests and contributions to the field:

Deep Classifier Mimicry without Data Access

Where is the Truth? The Risk of Getting Confounded in a Continual World

BOWLL: A Deceptively Simple Open World Lifelong Learner

Designing a Hybrid Neural System to Learn Real-world Crack Segmentation from Fractal-based Simulation

Probabilistic Circuits That Know What They Don't Know

Self expanding neural networks

A wholistic view of continual learning with deep neural networks: Forgotten lessons and the bridge to active and open world learning

Queer in AI: a case study in community-led participatory AI

Martin Mundt Information

University

Position

PhD candidate in Computer Science

Citations(all)

1075

Citations(since 2020)

764

Cited By

432

hIndex(all)

12

hIndex(since 2020)

11

i10Index(all)

13

i10Index(since 2020)

11

Email

University Profile Page

Goethe-Universität Frankfurt am Main

Google Scholar

View Google Scholar Profile

Martin Mundt Skills & Research Interests

neural networks

deep learning

continual learning

computer vision

Top articles of Martin Mundt

Title

Journal

Author(s)

Publication Date

Deep Classifier Mimicry without Data Access

Steven Braun

Martin Mundt

Kristian Kersting

2024/4/18

Where is the Truth? The Risk of Getting Confounded in a Continual World

arXiv preprint arXiv:2402.06434

Florian Peter Busch

Roshni Kamath

Rupert Mitchell

Wolfgang Stammer

Kristian Kersting

...

2024/2/9

BOWLL: A Deceptively Simple Open World Lifelong Learner

arXiv preprint arXiv:2402.04814

Roshni Kamath

Rupert Mitchell

Subarnaduti Paul

Kristian Kersting

Martin Mundt

2024/2/7

Designing a Hybrid Neural System to Learn Real-world Crack Segmentation from Fractal-based Simulation

Achref Jaziri

Martin Mundt

Andres Fernandez

Visvanathan Ramesh

2024

Probabilistic Circuits That Know What They Don't Know

Fabrizio Ventola

Steven Braun

Yu Zhongjie

Martin Mundt

Kristian Kersting

2023/7/2

Self expanding neural networks

arXiv preprint arXiv:2307.04526

Rupert Mitchell

Martin Mundt

Kristian Kersting

2023/7/10

A wholistic view of continual learning with deep neural networks: Forgotten lessons and the bridge to active and open world learning

Neural Networks

Martin Mundt

Yongwon Hong

Iuliia Pliushch

Visvanathan Ramesh

2023/3/1

Queer in AI: a case study in community-led participatory AI

Organizers Of Queerinai

Anaelia Ovalle

Arjun Subramonian

Ashwin Singh

Claas Voelcker

...

2023/6/12

Masked Autoencoders are Efficient Continual Federated Learners

arXiv preprint arXiv:2306.03542

Subarnaduti Paul

Lars-Joel Frey

Roshni Kamath

Kristian Kersting

Martin Mundt

2023/6/6

Benchmarking the Second Generation of Intel SGX for Machine Learning Workloads

Lectures Nots in Informatics (LNI), BTW 2023

Adrian Lutsch

Gagandeep Singh

Martin Mundt

Ragnar Mogk

Carsten Binnig

2023

Continual causality: A retrospective of the inaugural aaai-23 bridge program

Martin Mundt

Keiland W Cooper

Devendra Singh Dhami

Adéle Ribeiro

James Seale Smith

...

2023/6/4

FEATHERS: Federated Architecture and Hyperparameter Search

Jonas Seng

Pooja Prasad

Martin Mundt

Devendra Singh Dhami

Kristian Kersting

2023/3/27

Continual learning: Applications and the road forward

arXiv preprint arXiv:2311.11908

Eli Verwimp

Shai Ben-David

Matthias Bethge

Andrea Cossu

Alexander Gepperth

...

2023/11/20

Return of the normal distribution: Flexible deep continual learning with variational auto-encoders

Neural Networks

Yongwon Hong

Martin Mundt

Sungho Park

Yungjung Uh

Hyeran Byun

2022/10/1

Predictive whittle networks for time series

Zhongjie Yu

Fabrizio Ventola

Nils Thoma

Devendra Singh Dhami

Martin Mundt

...

2022/8/17

Unified Probabilistic Deep Continual Learning through Generative Replay and Open Set Recognition

Journal of Imaging

Martin Mundt

Iuliia Pliushch

Sagnik Majumder

Yongwon Hong

Visvanathan Ramesh

2022/3/31

CLEVA-Compass: A Continual Learning EValuation Assessment Compass to Promote Research Transparency and Comparability

Martin Mundt

Steven Lang

Quentin Delfosse

Kristian Kersting

2022/1/28

When deep classifiers agree: Analyzing correlations between learning order and image statistics

Iuliia Pliushch

Martin Mundt

Nicolas Lupp

Visvanathan Ramesh

2022/10/23

Towards Coreset Learning in Probabilistic Circuits

Martin Trapp

Steven Lang

Aastha Shah

Martin Mundt

Kristian Kersting

...

2022/8

Elevating Perceptual Sample Quality in PCs through Differentiable Sampling

Steven Lang

Martin Mundt

Fabrizio Ventola

Robert Peharz

Kristian Kersting

2022/10/5

See List of Professors in Martin Mundt University(Goethe-Universität Frankfurt am Main)

Co-Authors

H-index: 64
Kristian Kersting

Kristian Kersting

Technische Universität Darmstadt

H-index: 49
Visvanathan Ramesh

Visvanathan Ramesh

Goethe-Universität Frankfurt am Main

H-index: 6
Zhongjie Yu

Zhongjie Yu

Technische Universität Darmstadt

H-index: 6
Yong W. Hong

Yong W. Hong

Yonsei University

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