Mikkel N. Schmidt

88 papers A* 5A 2Misc 3Journal 39Unranked 39

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Blind Equalization Using a Variational Autoencoder With Second Order Volterra Channel Model. IEEE Trans. Cogn. Commun. Netw. Søren Føns Vind Nielsen, Darko Zibar, Mikkel N. Schmidt
2026	J	`jnl`	Practical Deep Heteroskedastic Regression. CoRR Mikkel Jordahn, Jonas Vestergaard Jensen, James Harrison, Michael Riis Andersen, Mikkel N. Schmidt
2025	J	`jnl`	Equivariant Neural Diffusion for Molecule Generation. CoRR François R. J. Cornet, Grigory Bartosh, Mikkel N. Schmidt, Christian A. Naesseth
2025	—	`conf`	FLEXtime: Filterbank Learning to Explain Time Series. xAI (4) Thea Brüsch, Kristoffer Knutsen Wickstrøm, Mikkel N. Schmidt, Robert Jenssen, Tommy Sonne Alstrøm
2025	—	`conf`	FreqRISE: Explaining time series using frequency masking. NLDL Thea Brüsch, Kristoffer Knutsen Wickstrøm, Mikkel N. Schmidt, Tommy Sonne Alstrøm, Robert Jenssen
2025	J	`jnl`	Improving generative inverse design of molecular catalysts in small data regime. Mach. Learn. Sci. Technol. François R. J. Cornet, Pratham Deshmukh, Bardi Benediktsson, Mikkel N. Schmidt, Arghya Bhowmik
2025	A*	`conf`	Kinetic Langevin Diffusion for Crystalline Materials Generation. ICML François R. J. Cornet, Federico Bergamin, Arghya Bhowmik, Juan Maria Garcia Lastra, Jes Frellsen, Mikkel N. Schmidt
2025	J	`jnl`	Kinetic Langevin Diffusion for Crystalline Materials Generation. CoRR François R. J. Cornet, Federico Bergamin, Arghya Bhowmik, Juan Maria Garcia Lastra, Jes Frellsen, Mikkel N. Schmidt
2025	—	`conf`	Mode Mismatch Mitigation in Gaussian-Modulated CV-QKD. ECOC Svitlana Matsenko, Amirhossein Ghazisaeidi, Marcin Jarzyna, Mikkel N. Schmidt, Søren F. Nielsen, Konrad Banaszek, Darko Zibar
2025	J	`jnl`	Mode Mismatch Mitigation in Gaussian-Modulated CV-QKD. CoRR Svitlana Matsenko, Amirhossein Ghazisaeidi, Marcin Jarzyna, Mikkel N. Schmidt, Søren F. Nielsen, Konrad Banaszek, Darko Zibar
2025	J	`jnl`	On Joint Regularization and Calibration in Deep Ensembles. CoRR Laurits Fredsgaard, Mikkel N. Schmidt
2025	J	`jnl`	On Joint Regularization and Calibration in Deep Ensembles. Trans. Mach. Learn. Res. Laurits Fredsgaard, Mikkel N. Schmidt
2025	A	`conf`	On Local Posterior Structure in Deep Ensembles. AISTATS Mikkel Jordahn, Jonas Vestergaard Jensen, Mikkel N. Schmidt, Michael Riis Andersen
2025	J	`jnl`	On Local Posterior Structure in Deep Ensembles. CoRR Mikkel Jordahn, Jonas Vestergaard Jensen, Mikkel N. Schmidt, Michael Riis Andersen
2025	—	`conf`	TNSPC: Learning from Partially Observed Data Using Tensor Network Structured Probabilistic Circuits. MLSP Niccolo' Ciolli, Morten Mørup, Mikkel N. Schmidt
2024	A*	`conf`	An improved analysis of per-sample and per-update clipping in federated learning. ICLR Bo Li, Xiaowen Jiang, Mikkel N. Schmidt, Tommy Sonne Alstrøm, Sebastian U. Stich
2024	J	`jnl`	Contrastive random lead coding for channel-agnostic self-supervision of biosignals. CoRR Thea Brüsch, Mikkel N. Schmidt, Tommy S. Alstrøm
2024	A*	`conf`	Equivariant Neural Diffusion for Molecule Generation. NeurIPS François R. J. Cornet, Grigory Bartosh, Mikkel N. Schmidt, Christian Andersson Naesseth
2024	J	`jnl`	Explaining time series models using frequency masking. CoRR Thea Brüsch, Kristoffer K. Wickstrøm, Mikkel N. Schmidt, Tommy S. Alstrøm, Robert Jenssen
2024	J	`jnl`	FLEXtime: Filterbank learning for explaining time series. CoRR Thea Brüsch, Kristoffer K. Wickstrøm, Mikkel N. Schmidt, Robert Jenssen, Tommy S. Alstrøm
2024	—	`conf`	Modeling Human Responses by Ordinal Archetypal Analysis. MLSP Anna Emilie J. Wedenborg, Michael Alexander Harborg, Andreas Bigom, Oliver Elmgreen, Marcus Presutti, Andreas Råskov, Fumiko Kano Glückstad, Mikkel N. Schmidt, Morten Mørup
2024	J	`jnl`	Modeling Human Responses by Ordinal Archetypal Analysis. CoRR Anna Emilie J. Wedenborg, Michael Alexander Harborg, Andreas Bigom, Oliver Elmgreen, Marcus Presutti, Andreas Råskov, Fumiko Kano Glückstad, Mikkel N. Schmidt, Morten Mørup
2024	J	`jnl`	Probabilistic PARAFAC2. Entropy Philip J. H. Jørgensen, Søren Føns Vind Nielsen, Jesper Løve Hinrich, Mikkel N. Schmidt, Kristoffer H. Madsen, Morten Mørup
2024	J	`jnl`	Synthetic data shuffling accelerates the convergence of federated learning under data heterogeneity. Trans. Mach. Learn. Res. Bo Li, Yasin Esfandiari, Mikkel N. Schmidt, Tommy Sonne Alstrøm, Sebastian U. Stich
2023	—	`conf`	Amortized Variational Peak Fitting For Spectroscopic Data. MLSP David Frich Hansen, Tommy Sonne Alstrøm, Mikkel N. Schmidt
2023	—	`conf`	Angular Central Gaussian and Watson Mixture Models for Assessing Dynamic Functional Brain Connectivity During a Motor Task. ICASSP Workshops Anders S. Olsen, Emil Ortvald, Kristoffer H. Madsen, Mikkel N. Schmidt, Morten Mørup
2023	J	`jnl`	Coherent energy and force uncertainty in deep learning force fields. CoRR Peter Bjørn Jørgensen, Jonas Busk, Ole Winther, Mikkel N. Schmidt
2023	J	`jnl`	Graph Neural Network Interatomic Potential Ensembles with Calibrated Aleatoric and Epistemic Uncertainty on Energy and Forces. CoRR Jonas Busk, Mikkel N. Schmidt, Ole Winther, Tejs Vegge, Peter Bjørn Jørgensen
2023	—	`conf`	Multi-View Self-Supervised Learning For Multivariate Variable-Channel Time Series. MLSP Thea Brüsch, Mikkel N. Schmidt, Tommy S. Alstrøm
2023	J	`jnl`	Multi-view self-supervised learning for multivariate variable-channel time series. CoRR Thea Brüsch, Mikkel N. Schmidt, Tommy S. Alstrøm
2023	A*	`conf`	On the Effectiveness of Partial Variance Reduction in Federated Learning with Heterogeneous Data. CVPR Bo Li, Mikkel N. Schmidt, Tommy S. Alstrøm, Sebastian U. Stich
2023	J	`jnl`	Synthetic data shuffling accelerates the convergence of federated learning under data heterogeneity. CoRR Bo Li, Yasin Esfandiari, Mikkel N. Schmidt, Tommy S. Alstrøm, Sebastian U. Stich
2022	—	`conf`	Bayesian dropout. ANT/EDI40 Tue Herlau, Mikkel N. Schmidt, Morten Mørup
2022	J	`jnl`	Calibrated uncertainty for molecular property prediction using ensembles of message passing neural networks. Mach. Learn. Sci. Technol. Jonas Busk, Peter Bjørn Jørgensen, Arghya Bhowmik, Mikkel N. Schmidt, Ole Winther, Tejs Vegge
2022	J	`jnl`	End-to-End Learning for VCSEL-based Optical Interconnects: State-of-the-Art, Challenges, and Opportunities. CoRR Muralikrishnan Srinivasan, Jinxiang Song, Alexander Grabowski, Krzysztof Szczerba, Holger K. Iversen, Mikkel N. Schmidt, Darko Zibar, Jochen Schröder, Anders Larsson, Christian Häger, Henk Wymeersch
2022	J	`jnl`	Partial Variance Reduction improves Non-Convex Federated learning on heterogeneous data. CoRR Bo Li, Mikkel N. Schmidt, Tommy S. Alstrøm, Sebastian U. Stich
2022	J	`jnl`	Raman Spectrum Matching with Contrastive Representation Learning. CoRR Bo Li, Mikkel N. Schmidt, Tommy S. Alstrøm
2021	J	`jnl`	Calibrated Uncertainty for Molecular Property Prediction using Ensembles of Message Passing Neural Networks. CoRR Jonas Busk, Peter Bjørn Jørgensen, Arghya Bhowmik, Mikkel N. Schmidt, Ole Winther, Tejs Vegge
2021	J	`jnl`	Matrix Product States for Inference in Discrete Probabilistic Models. J. Mach. Learn. Res. Rasmus Bonnevie, Mikkel N. Schmidt
2021	J	`jnl`	Using connectomics for predictive assessment of brain parcellations. NeuroImage Kristoffer Jon Albers, Karen Sandø Ambrosen, Matthew G. Liptrot, Tim B. Dyrby, Mikkel N. Schmidt, Morten Mørup
2020	J	`jnl`	Validation of structural brain connectivity networks: The impact of scanning parameters. NeuroImage Karen Sandø Ambrosen, Simon F. Eskildsen, Max Hinne, Kristine Krug, Henrik Lundell, Mikkel N. Schmidt, Marcel A. J. van Gerven, Morten Mørup, Tim B. Dyrby
2019	—	`conf`	A Bayesian Generative Model With Gaussian Process Priors For Thermomechanical Analysis Of Micro-Resonators. MLSP Maximillian Fornitz Vording, Peter O. Okeyo, Juan J. R. Guillamón, Peter E. Larsen, Mikkel N. Schmidt, Tommy S. Alstrøm
2019	Misc	`conf`	Peak Detection and Baseline Correction Using a Convolutional Neural Network. ICASSP Mikkel N. Schmidt, Tommy S. Alstrøm, Marcus Svendstorp, Jan Larsen
2018	J	`jnl`	Neural Message Passing with Edge Updates for Predicting Properties of Molecules and Materials. CoRR Peter Bjørn Jørgensen, Karsten Wedel Jacobsen, Mikkel N. Schmidt
2018	J	`jnl`	Predictive assessment of models for dynamic functional connectivity. NeuroImage Søren Føns Vind Nielsen, Mikkel N. Schmidt, Kristoffer Henriksen, Morten Mørup
2018	J	`jnl`	Probabilistic PARAFAC2. CoRR Philip J. H. Jørgensen, Søren Føns Vind Nielsen, Jesper Løve Hinrich, Mikkel N. Schmidt, Kristoffer Hougaard Madsen, Morten Mørup
2018	—	`conf`	Testing group differences in state transition structure of dynamic functional connectivity models. PRNI Søren Føns Vind Nielsen, Diego Vidaurre, Kristoffer Hougaard Madsen, Mikkel N. Schmidt, Morten Mørup
2018	—	`conf`	Understanding Mindsets Across Markets, Internationally: A Public-Private Innovation Project for Developing a Tourist Data Analytic Platform. COMPSAC (2) Kristoffer Jon Albers, Mikkel N. Schmidt, Morten Mørup, Marisciel Litong-Palima, Rasmus Bonnevie, Fumiko Kano Glückstad
2017	Misc	`conf`	A pseudo-Voigt component model for high-resolution recovery of constituent spectra in Raman spectroscopy. ICASSP Tommy S. Alstrøm, Mikkel N. Schmidt, Tomas Rindzevicius, Anja Boisen, Jan Larsen
2017	—	`conf`	Difference-of-Convex optimization for variational kl-corrected inference in dirichlet process mixtures. MLSP Rasmus Bonnevie, Mikkel N. Schmidt, Morten Mørup
2017	J	`jnl`	Infinite von Mises-Fisher Mixture Modeling of Whole Brain fMRI Data. Neural Comput. Rasmus Erbou Røge, Kristoffer Hougaard Madsen, Mikkel N. Schmidt, Morten Mørup
2017	—	`conf`	Modeling dynamic functional connectivity using a wishart mixture model. PRNI Søren Føns Vind Nielsen, Kristoffer Hougaard Madsen, Mikkel N. Schmidt, Morten Mørup
2017	Misc	`conf`	Scalable group level probabilistic sparse factor analysis. ICASSP Jesper Løve Hinrich, Søren Føns Vind Nielsen, Nicolai André Brogaard Riis, Casper T. Eriksen, Jacob Frosig, Marco D. F. Kristensen, Mikkel N. Schmidt, Kristoffer Hougaard Madsen, Morten Mørup
2016	—	`conf`	Bayesian latent feature modeling for modeling bipartite networks with overlapping groups. MLSP Philip H. Jørgensen, Morten Mørup, Mikkel N. Schmidt, Tue Herlau
2016	—	`conf`	Completely random measures for modelling block-structured sparse networks. NIPS Tue Herlau, Mikkel N. Schmidt, Morten Mørup
2016	—	`conf`	The influence of hyper-parameters in the infinite relational model. MLSP Kristoffer Jon Albers, Morten Mørup, Mikkel N. Schmidt
2015	—	`conf`	Numerical approximations for speeding up MCMC inference in the infinite relational model. EUSIPCO Mikkel N. Schmidt, Kristoffer Jon Albers
2015	—	`conf`	Unsupervised segmentation of task activated regions in fMRI. MLSP Rasmus Erbou Røge, Kristoffer Hougaard Madsen, Mikkel N. Schmidt, Morten Mørup
2014	J	`jnl`	Cross-categorization of legal concepts across boundaries of legal systems: in consideration of inferential links. Artif. Intell. Law Fumiko Kano Glückstad, Tue Herlau, Mikkel N. Schmidt, Morten Mørup
2014	—	`conf`	Discovering hierarchical structure in normal relational data. CIP Mikkel N. Schmidt, Tue Herlau, Morten Mørup
2014	J	`jnl`	Errata to "Bayesian Community Detection" ( Neural Comput. Morten Mørup, Mikkel N. Schmidt
2014	—	`conf`	Improving the robustness of Surface Enhanced Raman Spectroscopy based sensors by Bayesian Non-negative Matrix Factorization. MLSP Tommy S. Alstrøm, Kasper B. Frohling, Jan Larsen, Mikkel N. Schmidt, Michael Bache, Michael S. Schmidt, Mogens H. Jakobsen, Anja Boisen
2014	J	`jnl`	Non-parametric Bayesian graph models reveal community structure in resting state fMRI. NeuroImage Kasper Winther Andersen, Kristoffer Hougaard Madsen, Hartwig Roman Siebner, Mikkel N. Schmidt, Morten Mørup, Lars Kai Hansen
2014	—	`conf`	Nonparametric Bayesian clustering of structural whole brain connectivity in full image resolution. PRNI Karen Sandø Ambrosen, Kristoffer Jon Albers, Tim B. Dyrby, Mikkel N. Schmidt, Morten Mørup
2014	—	`conf`	Nonparametric statistical structuring of knowledge systems using binary feature matches. MLSP Morten Mørup, Fumiko Kano Glückstad, Tue Herlau, Mikkel N. Schmidt
2013	—	`conf`	Analysis of Conceptualization Patterns across Groups of People. TAAI Fumiko Kano Glückstad, Tue Herlau, Mikkel N. Schmidt, Morten Mørup, Rafal Rzepka, Kenji Araki
2013	—	`conf`	Comparing Structural Brain Connectivity by the Infinite Relational Model. PRNI Karen Sandø Ambrosen, Tue Herlau, Tim B. Dyrby, Mikkel N. Schmidt, Morten Mørup
2013	—	`conf`	Large scale inference in the Infinite Relational Model: Gibbs sampling is not enough. MLSP Kristoffer Jon Albers, Andreas Leon Aagaard Moth, Morten Mørup, Mikkel N. Schmidt
2013	—	`conf`	Modeling Temporal Evolution and Multiscale Structure in Networks. ICML (3) Tue Herlau, Morten Mørup, Mikkel N. Schmidt
2013	J	`jnl`	Nonparametric Bayesian Modeling of Complex Networks: An Introduction. IEEE Signal Process. Mag. Mikkel N. Schmidt, Morten Mørup
2013	—	`conf`	Unsupervised Knowledge Structuring: Application of Infinite Relational Models to the FCA Visualization. SITIS Fumiko Kano Glückstad, Tue Herlau, Mikkel N. Schmidt, Morten Mørup
2012	J	`jnl`	Bayesian Community Detection. Neural Comput. Morten Mørup, Mikkel N. Schmidt
2012	—	`conf`	Detecting hierarchical structure in networks. CIP Tue Herlau, Morten Mørup, Mikkel N. Schmidt, Lars Kai Hansen
2012	—	`conf`	Haussdorff and hellinger for colorimetric sensor array classification. MLSP Tommy S. Alstrøm, Bjørn Sand Jensen, Mikkel N. Schmidt, Natalie V. Kostesha, Jan Larsen
2012	—	`conf`	Modelling dense relational data. MLSP Tue Herlau, Morten Mørup, Mikkel N. Schmidt, Lars Kai Hansen
2011	J	`jnl`	Infinite Multiple Membership Relational Modeling for Complex Networks CoRR Morten Mørup, Mikkel N. Schmidt, Lars Kai Hansen
2011	—	`conf`	Infinite multiple membership relational modeling for complex networks. MLSP Morten Mørup, Mikkel N. Schmidt, Lars Kai Hansen
2011	—	`conf`	Transformation invariant sparse coding. MLSP Morten Mørup, Mikkel N. Schmidt
2011	J	`jnl`	Unmixing of Hyperspectral Images using Bayesian Non-negative Matrix Factorization with Volume Prior. J. Signal Process. Syst. Morten Arngren, Mikkel N. Schmidt, Jan Larsen
2010	—	`conf`	Infinite non-negative matrix factorization. EUSIPCO Mikkel N. Schmidt, Morten Mørup
2009	—	`conf`	Bayesian Non-negative Matrix Factorization. ICA Mikkel N. Schmidt, Ole Winther, Lars Kai Hansen
2009	A*	`conf`	Function factorization using warped Gaussian processes. ICML Mikkel N. Schmidt
2009	—	`conf`	Linearly constrained Bayesian matrix factorization for blind source separation. NIPS Mikkel N. Schmidt
2009	—	`conf`	Probabilistic non-negative tensor factorization using Markov chain Monte Carlo. EUSIPCO Mikkel N. Schmidt, Shakir Mohamed
2008	J	`jnl`	Nonnegative Matrix Factorization with Gaussian Process Priors. Comput. Intell. Neurosci. Mikkel N. Schmidt, Hans Laurberg
2008	—	`conf`	Structured non-negative matrix factorization with sparsity patterns. ACSCC Hans Laurberg, Mikkel N. Schmidt, Mads Græsbøll Christensen, Søren Holdt Jensen
2006	—	`conf`	Nonnegative Matrix Factor 2-D Deconvolution for Blind Single Channel Source Separation. ICA Mikkel N. Schmidt, Morten Mørup
2006	A	`conf`	Single-channel speech separation using sparse non-negative matrix factorization. INTERSPEECH Mikkel N. Schmidt, Rasmus Kongsgaard Olsson