Joachim M. Buhmann

ORCID

Publication Activity (10 Years)

Years Active: 1988-2024
Publications (10 Years): 89

Top Venues

Technical University Munich, Germany (PHD)

Education History

Technical University Munich, Germany

PHD

Publications

Xia Li, Runzhao Yang, Xiangtai Li, Antony J. Lomax, Ye Zhang, Joachim M. Buhmann
CPT-Interp: Continuous sPatial and Temporal Motion Modeling for 4D Medical Image Interpolation. CoRR (2024)
Omar G. Younis, Luca Corinzia, Ioannis N. Athanasiadis, Andreas Krause, Joachim M. Buhmann, Matteo Turchetta
Breeding Programs Optimization with Reinforcement Learning. CoRR (2024)
Marc Bartholet, Taehyeon Kim, Ami Beuret, Se-Young Yun, Joachim M. Buhmann
Non-linear Fusion in Federated Learning: A Hypernetwork Approach to Federated Domain Generalization. CoRR (2024)
Peifeng Jiang, Hong Liu, Xia Li, Ti Wang, Fabian Zhang, Joachim M. Buhmann
TAMBRIDGE: Bridging Frame-Centered Tracking and 3D Gaussian Splatting for Enhanced SLAM. CoRR (2024)
Xia Li, Muheng Li, Antony J. Lomax, Joachim M. Buhmann, Ye Zhang
Continuous sPatial-Temporal Deformable Image Registration (CPT-DIR) for motion modelling in radiotherapy: beyond classic voxel-based methods. CoRR (2024)
Mengyuan Liu, Zhongbin Fang, Xia Li, Joachim M. Buhmann, Xiangtai Li, Chen Change Loy
Point-In-Context: Understanding Point Cloud via In-Context Learning. CoRR (2024)
Robin C. Geyer, Alessandro Torcinovich, João B. S. Carvalho, Alexander Meyer, Joachim M. Buhmann
Measuring Orthogonality in Representations of Generative Models. CoRR (2024)
Jihe Li, Fabian Zhang, Xia Li, Tianhao Zhang, Ye Zhang, Joachim M. Buhmann
Gaussian Representation for Deformable Image Registration. CoRR (2024)
João B. S. Carvalho, Mengtao Zhang, Robin Geyer, Carlos Cotrini, Joachim M. Buhmann
Invariant Anomaly Detection under Distribution Shifts: A Causal Perspective. NeurIPS (2023)
Simon Föll, Alina Dubatovka, Eugen Ernst, Siu Lun Chau, Martin Maritsch, Patrik Okanovic, Gudrun Thäter, Joachim M. Buhmann, Felix Wortmann, Krikamol Muandet
Gated Domain Units for Multi-source Domain Generalization. Trans. Mach. Learn. Res. 2023 (2023)
Fabian Laumer, Mounir Amrani, Laura Manduchi, Ami Beuret, Lena Rubi, Alina Dubatovka, Christian M. Matter, Joachim M. Buhmann
Weakly supervised inference of personalized heart meshes based on echocardiography videos. Medical Image Anal. 83 (2023)
João B. S. Carvalho, Mengtao Zhang, Robin Geyer, Carlos Cotrini, Joachim M. Buhmann
Invariant Anomaly Detection under Distribution Shifts: A Causal Perspective. CoRR (2023)
Zhongbin Fang, Xiangtai Li, Xia Li, Joachim M. Buhmann, Chen Change Loy, Mengyuan Liu
Explore In-Context Learning for 3D Point Cloud Understanding. CoRR (2023)
Ivan Ovinnikov, Joachim M. Buhmann
Regularizing Adversarial Imitation Learning Using Causal Invariance. CoRR (2023)
Lukas Klein, João B. S. Carvalho, Mennatallah El-Assady, Paolo Penna, Joachim M. Buhmann, Paul F. Jaeger
Improving Explainability of Disentangled Representations using Multipath-Attribution Mappings. CoRR (2023)
Zhongbin Fang, Xiangtai Li, Xia Li, Joachim M. Buhmann, Chen Change Loy, Mengyuan Liu
Explore In-Context Learning for 3D Point Cloud Understanding. NeurIPS (2023)
Omar G. Younis, Matteo Turchetta, Daniel Ariza Suarez, Steven Yates, Bruno Studer, Ioannis N. Athanasiadis, Andreas Krause, Joachim M. Buhmann, Luca Corinzia
ChromaX: a fast and scalable breeding program simulator. Bioinform. 39 (12) (2023)
João B. S. Carvalho, Carlos Cotrini, Fabian Laumer, André Euler, Katharina Martini, Thomas Frauenfelder, Joachim M. Buhmann
Domain Generalization for Diagnosis of Pulmonary Fibrosis Using Dose-Invariant Feature Selection. ISBI (2023)
Matteo Turchetta, Luca Corinzia, Scott Sussex, Amanda Burton, Juan Herrera, Ioannis Athanasiadis, Joachim M. Buhmann, Andreas Krause
Learning Long-Term Crop Management Strategies with CyclesGym. NeurIPS (2022)
Lukas Klein, João B. S. Carvalho, Mennatallah El-Assady, Paolo Penna, Joachim M. Buhmann, Paul F. Jaeger
Improving Explainability of Disentangled Representations using Multipath-Attribution Mappings. MIDL (2022)
Eugene Bykovets, Yannick Metz, Mennatallah El-Assady, Daniel A. Keim, Joachim M. Buhmann
How to Enable Uncertainty Estimation in Proximal Policy Optimization. CoRR (2022)
Djorde Miladinovic, Kumar Shridhar, Kushal Jain, Max B. Paulus, Joachim M. Buhmann, Carl Allen
Learning to Drop Out: An Adversarial Approach to Training Sequence VAEs. CoRR (2022)
Djordje Miladinovic, Kumar Shridhar, Kushal Jain, Max B. Paulus, Joachim M. Buhmann, Carl Allen
Learning to Drop Out: An Adversarial Approach to Training Sequence VAEs. NeurIPS (2022)
Eugene Bykovets, Yannick Metz, Mennatallah El-Assady, Daniel A. Keim, Joachim M. Buhmann
BARReL: Bottleneck Attention for Adversarial Robustness in Vision-Based Reinforcement Learning. CoRR (2022)
Simon Föll, Alina Dubatovka, Eugen Ernst, Martin Maritsch, Patrik Okanovic, Gudrun Thäter, Joachim M. Buhmann, Felix Wortmann, Krikamol Muandet
Gated Domain Units for Multi-source Domain Generalization. CoRR (2022)
Luca Corinzia, Paolo Penna, Wojciech Szpankowski, Joachim M. Buhmann
Statistical and computational thresholds for the planted k-densest sub-hypergraph problem. AISTATS (2022)
João BS Carvalho, João A. Santinha, Djordje Miladinovic, Carlos Cotrini, Joachim M. Buhmann
Holistic Modeling In Medical Image Segmentation Using Spatial Recurrence. MIDL (2022)
Ðorðe Miladinovic, Aleksandar Stanic, Stefan Bauer, Jürgen Schmidhuber, Joachim M. Buhmann
Spatial Dependency Networks: Neural Layers for Improved Generative Image Modeling. ICLR (2021)
Luca Corinzia, Paolo Penna, Wojciech Szpankowski, Joachim M. Buhmann
On maximum-likelihood estimation in the all-or-nothing regime. ISIT (2021)
Daniel Paysan, Luis Haug, Michael Bajka, Markus Oelhafen, Joachim M. Buhmann
Self-supervised representation learning for surgical activity recognition. Int. J. Comput. Assist. Radiol. Surg. 16 (11) (2021)
João B. S. Carvalho, João A. Santinha, Djordje Miladinovic, Joachim M. Buhmann
Spatially Dependent U-Nets: Highly Accurate Architectures for Medical Imaging Segmentation. CoRR (2021)
Luca Corinzia, Paolo Penna, Wojciech Szpankowski, Joachim M. Buhmann
On maximum-likelihood estimation in the all-or-nothing regime. CoRR (2021)
Viktor Wegmayr, Joachim M. Buhmann
Entrack: Probabilistic Spherical Regression with Entropy Regularization for Fiber Tractography. Int. J. Comput. Vis. 129 (3) (2021)
Djordje Miladinovic, Aleksandar Stanic, Stefan Bauer, Jürgen Schmidhuber, Joachim M. Buhmann
Spatial Dependency Networks: Neural Layers for Improved Generative Image Modeling. CoRR (2021)
Luca Corinzia, Paolo Penna, Wojciech Szpankowski, Joachim M. Buhmann
Statistical and computational thresholds for the planted k-densest sub-hypergraph problem. CoRR (2020)
Luca Corinzia, Fabian Laumer, Alessandro Candreva, Maurizio Taramasso, Francesco Maisano, Joachim M. Buhmann
Neural collaborative filtering for unsupervised mitral valve segmentation in echocardiography. Artif. Intell. Medicine 110 (2020)
Aytunc Sahin, Yatao Bian, Joachim M. Buhmann, Andreas Krause
From Sets to Multisets: Provable Variational Inference for Probabilistic Integer Submodular Models. CoRR (2020)
Fabian Laumer, Gabriel Fringeli, Alina Dubatovka, Laura Manduchi, Joachim M. Buhmann
DeepHeartBeat: Latent trajectory learning of cardiac cycles using cardiac ultrasounds. ML4H@NeurIPS (2020)
Aytunc Sahin, Yatao Bian, Joachim M. Buhmann, Andreas Krause
From Sets to Multisets: Provable Variational Inference for Probabilistic Integer Submodular Models. ICML (2020)
Patrick Schwab, Lorenz Linhardt, Stefan Bauer, Joachim M. Buhmann, Walter Karlen
Learning Counterfactual Representations for Estimating Individual Dose-Response Curves. AAAI (2020)
Yatao Bian, Joachim M. Buhmann, Andreas Krause
Continuous Submodular Function Maximization. CoRR (2020)
Luca Corinzia, Fabian Laumer, Alessandro Candreva, Maurizio Taramasso, Francesco Maisano, Joachim M. Buhmann
Neural collaborative filtering for unsupervised mitral valve segmentation in echocardiography. CoRR (2020)
Viktor Wegmayr, Aytunc Sahin, Björn Sæmundsson, Joachim M. Buhmann
Instance Segmentation for the Quantification of Microplastic Fiber Images. WACV (2020)
Luca Corinzia, Paolo Penna, Luca Mondada, Joachim M. Buhmann
Exact Recovery for a Family of Community-Detection Generative Models. ISIT (2019)
Yatao An Bian, Joachim M. Buhmann, Andreas Krause
Optimal Continuous DR-Submodular Maximization and Applications to Provable Mean Field Inference. ICML (2019)
Luca Corinzia, Paolo Penna, Luca Mondada, Joachim M. Buhmann
Exact Recovery for a Family of Community-Detection Generative Models. CoRR (2019)
Viktor Wegmayr, Maurice Hörold, Joachim M. Buhmann
Generative Aging Of Brain MRI For Early Prediction Of MCI-AD Conversion. ISBI (2019)
Ðorðe Miladinovic, Muhammad Waleed Gondal, Bernhard Schölkopf, Joachim M. Buhmann, Stefan Bauer
Disentangled State Space Models: Unsupervised Learning of dynamics across Heterogeneous Environments. DGS@ICLR (2019)
Luca Corinzia, Joachim M. Buhmann
Variational Federated Multi-Task Learning. CoRR (2019)
Luca Corinzia, Jesse Provost, Alessandro Candreva, Maurizio Tamarasso, Francesco Maisano, Joachim M. Buhmann
Unsupervised Mitral Valve Segmentation in Echocardiography with Neural Network Matrix Factorization. AIME (2019)
Ðorðe Miladinovic, Christine Muheim, Stefan Bauer, Andrea Spinnler, Daniela Noain, Mojtaba Bandarabadi, Benjamin Gallusser, Gabriel Krummenacher, Christian R. Baumann, Antoine Adamantidis, Steven A. Brown, Joachim M. Buhmann
SPINDLE: End-to-end learning from EEG/EMG to extrapolate animal sleep scoring across experimental settings, labs and species. PLoS Comput. Biol. 15 (4) (2019)
Ðorðe Miladinovic, Muhammad Waleed Gondal, Bernhard Schölkopf, Joachim M. Buhmann, Stefan Bauer
Disentangled State Space Representations. CoRR (2019)
Viktor Wegmayr, Maurice Hörold, Joachim M. Buhmann
Generative Aging of Brain MR-Images and Prediction of Alzheimer Progression. GCPR (2019)
Philippe Wenk, Alkis Gotovos, Stefan Bauer, Nico S. Gorbach, Andreas Krause, Joachim M. Buhmann
Fast Gaussian process based gradient matching for parameter identification in systems of nonlinear ODEs. AISTATS (2019)
Patrick Schwab, Lorenz Linhardt, Stefan Bauer, Joachim M. Buhmann, Walter Karlen
Learning Counterfactual Representations for Estimating Individual Dose-Response Curves. CoRR (2019)
Viktor Wegmayr, Giacomo Giuliari, Joachim M. Buhmann
Entrack: A Data-Driven Maximum-Entropy Approach to Fiber Tractography. GCPR (2019)
An Bian, Joachim M. Buhmann, Andreas Krause
Optimal DR-Submodular Maximization and Applications to Provable Mean Field Inference. CoRR (2018)
Joachim M. Buhmann, Julien Dumazert, Alexey Gronskiy, Wojciech Szpankowski
Posterior agreement for large parameter-rich optimization problems. Theor. Comput. Sci. 745 (2018)
Philippe Wenk, Alkis Gotovos, Stefan Bauer, Nico S. Gorbach, Andreas Krause, Joachim M. Buhmann
Fast Gaussian Process Based Gradient Matching for Parameter Identification in Systems of Nonlinear ODEs. CoRR (2018)
Viktor Wegmayr, Giacomo Giuliari, Stefan Holdener, Joachim M. Buhmann
Data-driven fiber tractography with neural networks. ISBI (2018)
Joachim M. Buhmann
VIS Capstone Address : Can I believe what I see?-Information theoretic algorithm validation. VAST (2018)
Gabriel Krummenacher, Cheng Soon Ong, Stefan Koller, Seijin Kobayashi, Joachim M. Buhmann
Wheel Defect Detection With Machine Learning. IEEE Trans. Intell. Transp. Syst. 19 (4) (2018)
Stefan Frässle, Ekaterina I. Lomakina, Lars Kasper, Zina M. Manjaly, Alexander P. Leff, Klaas P. Pruessmann, Joachim M. Buhmann, Klaas E. Stephan
A generative model of whole-brain effective connectivity. NeuroImage 179 (2018)
Viktor Wegmayr, Sai Aitharaju, Joachim M. Buhmann
Classification of brain MRI with big data and deep 3D convolutional neural networks. Medical Imaging: Computer-Aided Diagnosis (2018)
Nico S. Gorbach, Marc Tittgemeyer, Joachim M. Buhmann
Pipeline validation for connectivity-based cortex parcellation. NeuroImage 181 (2018)
Alexey Gronskiy, Joachim M. Buhmann, Wojciech Szpankowski
Free Energy Asymptotics for Problems with Weak Solution Dependencies. ISIT (2018)
Joachim M. Buhmann, Alexey Gronskiy, Matús Mihalák, Tobias Pröger, Rastislav Srámek, Peter Widmayer
Robust optimization in the presence of uncertainty: A generic approach. J. Comput. Syst. Sci. 94 (2018)
Andrew An Bian, Joachim M. Buhmann, Andreas Krause, Sebastian Tschiatschek
Guarantees for Greedy Maximization of Non-submodular Functions with Applications. CoRR (2017)
Julian G. Zilly, Joachim M. Buhmann, Dwarikanath Mahapatra
Glaucoma detection using entropy sampling and ensemble learning for automatic optic cup and disc segmentation. Comput. Medical Imaging Graph. 55 (2017)
Nico S. Gorbach, Stefan Bauer, Joachim M. Buhmann
Scalable Variational Inference for Dynamical Systems. NIPS (2017)
Gabriele Abbati, Stefan Bauer, Sebastian Winklhofer, Peter J. Schüffler, Ulrike Held, Jakob M. Burgstaller, Johann Steurer, Joachim M. Buhmann
MRI-Based Surgical Planning for Lumbar Spinal Stenosis. MICCAI (3) (2017)
Stefan Bauer, Nico S. Gorbach, Ðorðe Miladinovic, Joachim M. Buhmann
Efficient and Flexible Inference for Stochastic Systems. NIPS (2017)
An Bian, Kfir Yehuda Levy, Andreas Krause, Joachim M. Buhmann
Non-monotone Continuous DR-submodular Maximization: Structure and Algorithms. NIPS (2017)
Stefan Frässle, Ekaterina I. Lomakina, Adeel Razi, Karl J. Friston, Joachim M. Buhmann, Klaas E. Stephan
Regression DCM for fMRI. NeuroImage 155 (2017)
Joachim M. Buhmann, Julien Dumazert, Alexey Gronskiy, Wojciech Szpankowski
Phase Transitions in Parameter Rich Optimization Problems. ANALCO (2017)
Andrew An Bian, Joachim M. Buhmann, Andreas Krause, Sebastian Tschiatschek
Guarantees for Greedy Maximization of Non-submodular Functions with Applications. ICML (2017)
An Bian, Kfir Y. Levy, Andreas Krause, Joachim M. Buhmann
Non-monotone Continuous DR-submodular Maximization: Structure and Algorithms. CoRR (2017)
Andrew An Bian, Baharan Mirzasoleiman, Joachim M. Buhmann, Andreas Krause
Guaranteed Non-convex Optimization: Submodular Maximization over Continuous Domains. AISTATS (2017)
Nico S. Gorbach, Andrew An Bian, Benjamin Fischer, Stefan Bauer, Joachim M. Buhmann
Model Selection for Gaussian Process Regression. GCPR (2017)
Gabriel Krummenacher, Brian McWilliams, Yannic Kilcher, Joachim M. Buhmann, Nicolai Meinshausen
Scalable Adaptive Stochastic Optimization Using Random Projections. NIPS (2016)
Gabriel Krummenacher, Brian McWilliams, Yannic Kilcher, Joachim M. Buhmann, Nicolai Meinshausen
Scalable Adaptive Stochastic Optimization Using Random Projections. CoRR (2016)
Thomas J. Fuchs, Joachim M. Buhmann
Computational Pathology: Challenges and Promises for Tissue Analysis. CoRR (2016)
Andrew An Bian, Baharan Mirzasoleiman, Joachim M. Buhmann, Andreas Krause
Guaranteed Non-convex Optimization: Submodular Maximization over Continuous Domains. CoRR (2016)
Dmitry Laptev, Nikolay Savinov, Joachim M. Buhmann, Marc Pollefeys
TI-POOLING: transformation-invariant pooling for feature learning in Convolutional Neural Networks. CoRR (2016)
Yatao Bian, Alexey Gronskiy, Joachim M. Buhmann
Greedy MAXCUT Algorithms and their Information Content. CoRR (2016)
Dwarikanath Mahapatra, Franciscus M. Vos, Joachim M. Buhmann
Active learning based segmentation of Crohns disease from abdominal MRI. Comput. Methods Programs Biomed. 128 (2016)
Yatao Bian, Alexey Gronskiy, Joachim M. Buhmann
Information-theoretic analysis of MaxCut algorithms. ITA (2016)
Stefan Bauer, Nicolas Carion, Peter J. Schüffler, Thomas J. Fuchs, Peter J. Wild, Joachim M. Buhmann
Multi-Organ Cancer Classification and Survival Analysis. CoRR (2016)
Dmitry Laptev, Nikolay Savinov, Joachim M. Buhmann, Marc Pollefeys
TI-POOLING: Transformation-Invariant Pooling for Feature Learning in Convolutional Neural Networks. CVPR (2016)
Andreas P. Streich, Joachim M. Buhmann
Asymptotic analysis of estimators on multi-label data. Mach. Learn. 99 (3) (2015)
Dwarikanath Mahapatra, Joachim M. Buhmann
Visual Saliency Based Active Learning for Prostate MRI Segmentation. MLMI (2015)
Dwarikanath Mahapatra, Joachim M. Buhmann
A field of experts model for optic cup and disc segmentation from retinal fundus images. ISBI (2015)
Dwarikanath Mahapatra, Zhang Li, Frans Vos, Joachim M. Buhmann
Joint segmentation and groupwise registration of cardiac DCE MRI using sparse data representations. ISBI (2015)
Dwarikanath Mahapatra, Peter J. Schüffler, Frans Vos, Joachim M. Buhmann
Crohn's disease segmentation from MRI using learned image priors. ISBI (2015)
David Balduzzi, Hastagiri Vanchinathan, Joachim M. Buhmann
Kickback Cuts Backprop's Red-Tape: Biologically Plausible Credit Assignment in Neural Networks. AAAI (2015)
Dmitry Laptev, Joachim M. Buhmann
Transformation-Invariant Convolutional Jungles. CVPR (2015)
Ekaterina I. Lomakina, Saee Paliwal, Andreea Oliviana Diaconescu, Kay Henning Brodersen, Eduardo A. Aponte, Joachim M. Buhmann, Klaas E. Stephan
Inversion of hierarchical Bayesian models using Gaussian processes. NeuroImage 118 (2015)
Yatao Bian, Alexey Gronskiy, Joachim M. Buhmann
Greedy MaxCut algorithms and their information content. ITW (2015)
Julian G. Zilly, Joachim M. Buhmann, Dwarikanath Mahapatra
Boosting Convolutional Filters with Entropy Sampling for Optic Cup and Disc Image Segmentation from Fundus Images. MLMI (2015)
Dmitry Laptev, A. Veznevets, Joachim M. Buhmann
Superslicing frame restoration for anisotropic sstem. ISBI (2014)

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Publication Activity (10 Years)

Top Topics

Top Venues

Joachim M. Buhmann