Mikkel N. Schmidt

Orcid: 0000-0001-6927-8869

According to our database1, Mikkel N. Schmidt authored at least 62 papers between 2006 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2023
Coherent energy and force uncertainty in deep learning force fields.
CoRR, 2023

Synthetic data shuffling accelerates the convergence of federated learning under data heterogeneity.
CoRR, 2023

Graph Neural Network Interatomic Potential Ensembles with Calibrated Aleatoric and Epistemic Uncertainty on Energy and Forces.
CoRR, 2023

Amortized Variational Peak Fitting For Spectroscopic Data.
Proceedings of the 33rd IEEE International Workshop on Machine Learning for Signal Processing, 2023

Multi-View Self-Supervised Learning For Multivariate Variable-Channel Time Series.
Proceedings of the 33rd IEEE International Workshop on Machine Learning for Signal Processing, 2023

Angular Central Gaussian and Watson Mixture Models for Assessing Dynamic Functional Brain Connectivity During a Motor Task.
Proceedings of the IEEE International Conference on Acoustics, 2023

On the Effectiveness of Partial Variance Reduction in Federated Learning with Heterogeneous Data.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
Calibrated uncertainty for molecular property prediction using ensembles of message passing neural networks.
Mach. Learn. Sci. Technol., 2022

Partial Variance Reduction improves Non-Convex Federated learning on heterogeneous data.
CoRR, 2022

End-to-End Learning for VCSEL-based Optical Interconnects: State-of-the-Art, Challenges, and Opportunities.
CoRR, 2022

Raman Spectrum Matching with Contrastive Representation Learning.
CoRR, 2022

Bayesian dropout.
Proceedings of the 13th International Conference on Ambient Systems, 2022

2021
Using connectomics for predictive assessment of brain parcellations.
NeuroImage, 2021

Matrix Product States for Inference in Discrete Probabilistic Models.
J. Mach. Learn. Res., 2021

Programmatic Policy Extraction by Iterative Local Search.
Proceedings of the Inductive Logic Programming - 30th International Conference, 2021

2020
Validation of structural brain connectivity networks: The impact of scanning parameters.
NeuroImage, 2020

2019
A Bayesian Generative Model With Gaussian Process Priors For Thermomechanical Analysis Of Micro-Resonators.
Proceedings of the 29th IEEE International Workshop on Machine Learning for Signal Processing, 2019

Peak Detection and Baseline Correction Using a Convolutional Neural Network.
Proceedings of the IEEE International Conference on Acoustics, 2019

2018
Predictive assessment of models for dynamic functional connectivity.
NeuroImage, 2018

Probabilistic PARAFAC2.
CoRR, 2018

Neural Message Passing with Edge Updates for Predicting Properties of Molecules and Materials.
CoRR, 2018

Testing group differences in state transition structure of dynamic functional connectivity models.
Proceedings of the 2018 International Workshop on Pattern Recognition in Neuroimaging, 2018

Understanding Mindsets Across Markets, Internationally: A Public-Private Innovation Project for Developing a Tourist Data Analytic Platform.
Proceedings of the 2018 IEEE 42nd Annual Computer Software and Applications Conference, 2018

2017
Infinite von Mises-Fisher Mixture Modeling of Whole Brain fMRI Data.
Neural Comput., 2017

Modeling dynamic functional connectivity using a wishart mixture model.
Proceedings of the 2017 International Workshop on Pattern Recognition in Neuroimaging, 2017

Difference-of-Convex optimization for variational kl-corrected inference in dirichlet process mixtures.
Proceedings of the 27th IEEE International Workshop on Machine Learning for Signal Processing, 2017

Scalable group level probabilistic sparse factor analysis.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

A pseudo-Voigt component model for high-resolution recovery of constituent spectra in Raman spectroscopy.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

2016
Completely random measures for modelling block-structured sparse networks.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Bayesian latent feature modeling for modeling bipartite networks with overlapping groups.
Proceedings of the 26th IEEE International Workshop on Machine Learning for Signal Processing, 2016

The influence of hyper-parameters in the infinite relational model.
Proceedings of the 26th IEEE International Workshop on Machine Learning for Signal Processing, 2016

2015
Unsupervised segmentation of task activated regions in fMRI.
Proceedings of the 25th IEEE International Workshop on Machine Learning for Signal Processing, 2015

Numerical approximations for speeding up MCMC inference in the infinite relational model.
Proceedings of the 23rd European Signal Processing Conference, 2015

2014
Non-parametric Bayesian graph models reveal community structure in resting state fMRI.
NeuroImage, 2014

Errata to "Bayesian Community Detection" (<i>Neural Computation</i>, Sept. 2012 , Vol. 24, No. 9: 2434-2456).
Neural Comput., 2014

Cross-categorization of legal concepts across boundaries of legal systems: in consideration of inferential links.
Artif. Intell. Law, 2014

Nonparametric Bayesian clustering of structural whole brain connectivity in full image resolution.
Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2014

Nonparametric statistical structuring of knowledge systems using binary feature matches.
Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2014

Improving the robustness of Surface Enhanced Raman Spectroscopy based sensors by Bayesian Non-negative Matrix Factorization.
Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2014

Discovering hierarchical structure in normal relational data.
Proceedings of the 4th International Workshop on Cognitive Information Processing, 2014

2013
Nonparametric Bayesian Modeling of Complex Networks: An Introduction.
IEEE Signal Process. Mag., 2013

Analysis of Conceptualization Patterns across Groups of People.
Proceedings of the Conference on Technologies and Applications of Artificial Intelligence, 2013

Unsupervised Knowledge Structuring: Application of Infinite Relational Models to the FCA Visualization.
Proceedings of the Ninth International Conference on Signal-Image Technology & Internet-Based Systems, 2013

Comparing Structural Brain Connectivity by the Infinite Relational Model.
Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2013

Large scale inference in the Infinite Relational Model: Gibbs sampling is not enough.
Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2013

Modeling Temporal Evolution and Multiscale Structure in Networks.
Proceedings of the 30th International Conference on Machine Learning, 2013

2012
Bayesian Community Detection.
Neural Comput., 2012

Modelling dense relational data.
Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2012

Haussdorff and hellinger for colorimetric sensor array classification.
Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2012

Detecting hierarchical structure in networks.
Proceedings of the 3rd International Workshop on Cognitive Information Processing, 2012

2011
Unmixing of Hyperspectral Images using Bayesian Non-negative Matrix Factorization with Volume Prior.
J. Signal Process. Syst., 2011

Infinite multiple membership relational modeling for complex networks.
Proceedings of the 2011 IEEE International Workshop on Machine Learning for Signal Processing, 2011

Transformation invariant sparse coding.
Proceedings of the 2011 IEEE International Workshop on Machine Learning for Signal Processing, 2011

2010
Infinite non-negative matrix factorization.
Proceedings of the 18th European Signal Processing Conference, 2010

2009
Linearly constrained Bayesian matrix factorization for blind source separation.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Bayesian Non-negative Matrix Factorization.
Proceedings of the Independent Component Analysis and Signal Separation, 2009

Function factorization using warped Gaussian processes.
Proceedings of the 26th Annual International Conference on Machine Learning, 2009

Probabilistic non-negative tensor factorization using Markov chain Monte Carlo.
Proceedings of the 17th European Signal Processing Conference, 2009

2008
Nonnegative Matrix Factorization with Gaussian Process Priors.
Comput. Intell. Neurosci., 2008

Structured non-negative matrix factorization with sparsity patterns.
Proceedings of the 42nd Asilomar Conference on Signals, Systems and Computers, 2008

2006
Single-channel speech separation using sparse non-negative matrix factorization.
Proceedings of the INTERSPEECH 2006, 2006

Nonnegative Matrix Factor 2-D Deconvolution for Blind Single Channel Source Separation.
Proceedings of the Independent Component Analysis and Blind Signal Separation, 2006


  Loading...