Jakub M. Tomczak

CoRR, 2024

Variational Stochastic Gradient Descent for Deep Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2024

Mixed Models with Multiple Instance Learning.

[BibT_eX]

[DOI]

Francesco Paolo Casale

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Deep Generative Modeling, Second Editiontion

[BibT_eX]

[DOI]

Springer, ISBN: 978-3-031-64086-5, 2024

2023

Attention-based Multi-instance Mixed Models.

[BibT_eX]

[DOI]

Francesco Paolo Casale

CoRR, 2023

De Novo Drug Design with Joint Transformers.

[BibT_eX]

[DOI]

Adam Izdebski

Ewa Szczurek

CoRR, 2023

Lamarck's Revenge: Inheritance of Learned Traits Can Make Robot Evolution Better.

[BibT_eX]

[DOI]

CoRR, 2023

Exploring Continual Learning of Diffusion Models.

[BibT_eX]

[DOI]

CoRR, 2023

Analyzing the Posterior Collapse in Hierarchical Variational Autoencoders.

[BibT_eX]

[DOI]

CoRR, 2023

A Comparison of Controller Architectures and Learning Mechanisms for Arbitrary Robot Morphologies.

[BibT_eX]

[DOI]

Proceedings of the IEEE Symposium Series on Computational Intelligence, 2023

Learning Data Representations with Joint Diffusion Models.

[BibT_eX]

[DOI]

Kamil Deja

Tomasz Trzcinski

Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

A-NeSI: A Scalable Approximate Method for Probabilistic Neurosymbolic Inference.

[BibT_eX]

[DOI]

Emile van Krieken

Thiviyan Thanapalasingam

Frank van Harmelen

Annette ten Teije

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Modelling Long Range Dependencies in $N$D: From Task-Specific to a General Purpose CNN.

[BibT_eX]

[DOI]

Mark Hoogendoorn

Jan-Jakob Sonke

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Continuous Kendall Shape Variational Autoencoders.

[BibT_eX]

[DOI]

Sharvaree P. Vadgama

Erik J. Bekkers

Proceedings of the Geometric Science of Information - 6th International Conference, 2023

2022

Time efficiency in optimization with a bayesian-Evolutionary algorithm.

[BibT_eX]

[DOI]

Swarm Evol. Comput., 2022

The Effects of Learning in Morphologically Evolving Robot Systems.

[BibT_eX]

[DOI]

Frontiers Robotics AI, 2022

Towards a General Purpose CNN for Long Range Dependencies in ND.

[BibT_eX]

[DOI]

CoRR, 2022

Defending Variational Autoencoders from Adversarial Attacks with MCMC.

[BibT_eX]

[DOI]

CoRR, 2022

Alleviating Adversarial Attacks on Variational Autoencoders with MCMC.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

On Analyzing Generative and Denoising Capabilities of Diffusion-based Deep Generative Models.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

CKConv: Continuous Kernel Convolution For Sequential Data.

[BibT_eX]

[DOI]

David W. Romero

Erik J. Bekkers

Mark Hoogendoorn

Proceedings of the Tenth International Conference on Learning Representations, 2022

FlexConv: Continuous Kernel Convolutions With Differentiable Kernel Sizes.

[BibT_eX]

[DOI]

David W. Romero

Robert-Jan Bruintjes

Erik J. Bekkers

Mark Hoogendoorn

Jan van Gemert

Proceedings of the Tenth International Conference on Learning Representations, 2022

Deep Generative Modeling

[BibT_eX]

[DOI]

Springer, ISBN: 978-3-030-93157-5, 2022

2021

Learning locomotion skills in evolvable robots.

[BibT_eX]

[DOI]

Neurocomputing, 2021

Self-Supervised Variational Auto-Encoders.

[BibT_eX]

[DOI]

Ioannis Gatopoulos

Entropy, 2021

Approximate Bayesian Computation for Discrete Spaces.

[BibT_eX]

[DOI]

Ilze Amanda Auzina

Entropy, 2021

Training Deep Spiking Auto-encoders without Bursting or Dying Neurons through Regularization.

[BibT_eX]

[DOI]

Justus F. Hübotter

Pablo Lanillos

CoRR, 2021

The Effects of Learning in Morphologically Evolving Robot Systems.

[BibT_eX]

[DOI]

Jie Luo

Ágoston E. Eiben

CoRR, 2021

Diagnosing Vulnerability of Variational Auto-Encoders to Adversarial Attacks.

[BibT_eX]

[DOI]

CoRR, 2021

Deep learning for white cabbage seedling prediction.

[BibT_eX]

[DOI]

Yura Perugachi-Diaz

Sandjai Bhulai

Comput. Electron. Agric., 2021

M2R: a Python add-on to cobrapy for modifying human genome-scale metabolic reconstruction using the gut microbiota models.

[BibT_eX]

[DOI]

Stanley Brul

Bioinform., 2021

Learning directed locomotion in modular robots with evolvable morphologies.

[BibT_eX]

[DOI]

Appl. Soft Comput., 2021

Invertible DenseNets with Concatenated LipSwish.

[BibT_eX]

[DOI]

Yura Perugachi-Diaz

Sandjai Bhulai

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Storchastic: A Framework for General Stochastic Automatic Differentiation.

[BibT_eX]

[DOI]

Emile van Krieken

Annette ten Teije

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Selecting Data Augmentation for Simulating Interventions.

[BibT_eX]

[DOI]

Patrick Forré

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

General Invertible Transformations for Flow-based Generative Modeling.

[BibT_eX]

[DOI]

CoRR, 2020

ABC-Di: Approximate Bayesian Computation for Discrete Data.

[BibT_eX]

[DOI]

Ilze Amanda Auzina

CoRR, 2020

Population-based Optimization for Kinetic Parameter Identification in Glycolytic Pathway in Saccharomyces cerevisiae.

[BibT_eX]

[DOI]

Ágoston E. Eiben

Stanley Brul

CoRR, 2020

i-DenseNets.

[BibT_eX]

[DOI]

Yura Perugachi-Diaz

Sandjai Bhulai

CoRR, 2020

Wavelet Networks: Scale Equivariant Learning From Raw Waveforms.

[BibT_eX]

[DOI]

CoRR, 2020

Super-resolution Variational Auto-Encoders.

[BibT_eX]

[DOI]

Ioannis Gatopoulos

Maarten Stol

CoRR, 2020

Designing Data Augmentation for Simulating Interventions.

[BibT_eX]

[DOI]

Patrick Forré

CoRR, 2020

Learning Discrete Distributions by Dequantization.

[BibT_eX]

[DOI]

Emiel Hoogeboom

Taco S. Cohen

CoRR, 2020

The Convolution Exponential and Generalized Sylvester Flows.

[BibT_eX]

[DOI]

Emiel Hoogeboom

Victor Garcia Satorras

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Generative Fourier-Based Auto-encoders: Preliminary Results.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning, Optimization, and Data Science, 2020

DIVA: Domain Invariant Variational Autoencoders.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Medical Imaging with Deep Learning, 2020

Attentive Group Equivariant Convolutional Networks.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

Differential Evolution with Reversible Linear Transformations.

[BibT_eX]

[DOI]

Ágoston E. Eiben

Proceedings of the GECCO '20: Genetic and Evolutionary Computation Conference, 2020

Evolutionary Algorithm with Non-parametric Surrogate Model for Tensor Program optimization.

[BibT_eX]

[DOI]

Proceedings of the IEEE Congress on Evolutionary Computation, 2020

2019

Low-Dimensional Perturb-and-MAP Approach for Learning Restricted Boltzmann Machines.

[BibT_eX]

[DOI]

Neural Process. Lett., 2019

Increasing Expressivity of a Hyperspherical VAE.

[BibT_eX]

[DOI]

Tim R. Davidson

Efstratios Gavves

CoRR, 2019

Simulating Execution Time of Tensor Programs using Graph Neural Networks.

[BibT_eX]

[DOI]

Romain Lepert

Auke J. Wiggers

CoRR, 2019

Combinatorial Bayesian Optimization using Graph Representations.

[BibT_eX]

[DOI]

CoRR, 2019

Combinatorial Bayesian Optimization using the Graph Cartesian Product.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

DIVA: Domain Invariant Variational Autoencoder.

[BibT_eX]

[DOI]

Proceedings of the Deep Generative Models for Highly Structured Data, 2019

Video Compression With Rate-Distortion Autoencoders.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

2018

Hierarchical VampPrior Variational Fair Auto-Encoder.

[BibT_eX]

[DOI]

Philip Botros

CoRR, 2018

Interaction prediction in structure-based virtual screening using deep learning.

[BibT_eX]

[DOI]

Comput. Biol. Medicine, 2018

Hyperspherical Variational Auto-Encoders.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Sylvester Normalizing Flows for Variational Inference.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Attention-based Deep Multiple Instance Learning.

[BibT_eX]

[DOI]

Proceedings of the 35th International Conference on Machine Learning, 2018

VAE with a VampPrior.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017

Learning Invariant Features Using Subspace Restricted Boltzmann Machine.

[BibT_eX]

[DOI]

Neural Process. Lett., 2017

Deep Learning with Permutation-invariant Operator for Multi-instance Histopathology Classification.

[BibT_eX]

[DOI]

CoRR, 2017

2016

Learning Informative Features from Restricted Boltzmann Machines.

[BibT_eX]

[DOI]

Neural Process. Lett., 2016

Articulated tracking with manifold regularized particle filter.

[BibT_eX]

[DOI]

Mach. Vis. Appl., 2016

Ensemble boosted trees with synthetic features generation in application to bankruptcy prediction.

[BibT_eX]

[DOI]

Sebastian K. Tomczak

Expert Syst. Appl., 2016

Improving Variational Auto-Encoders using Householder Flow.

[BibT_eX]

[DOI]

CoRR, 2016

Learning Deep Architectures for Interaction Prediction in Structure-based Virtual Screening.

[BibT_eX]

[DOI]

CoRR, 2016

Self-paced Learning for Imbalanced Data.

[BibT_eX]

[DOI]

Jerzy Swiatek

Proceedings of the Intelligent Information and Database Systems - 8th Asian Conference, 2016

2015

Boosted SVM with active learning strategy for imbalanced data.

[BibT_eX]

[DOI]

Soft Comput., 2015

Probabilistic combination of classification rules and its application to medical diagnosis.

[BibT_eX]

[DOI]

Mach. Learn., 2015

Classification Restricted Boltzmann Machine for comprehensible credit scoring model.

[BibT_eX]

[DOI]

Expert Syst. Appl., 2015

Improving neural networks with bunches of neurons modeled by Kumaraswamy units: Preliminary study.

[BibT_eX]

[DOI]

CoRR, 2015

RBM-SMOTE: Restricted Boltzmann Machines for Synthetic Minority Oversampling Technique.

[BibT_eX]

[DOI]

Proceedings of the Intelligent Information and Database Systems - 7th Asian Conference, 2015

2014

Subspace Restricted Boltzmann Machine.

[BibT_eX]

[DOI]

CoRR, 2014

Boosted SVM for extracting rules from imbalanced data in application to prediction of the post-operative life expectancy in the lung cancer patients.

[BibT_eX]

[DOI]

Appl. Soft Comput., 2014

Selecting right questions with Restricted Boltzmann Machines.

[BibT_eX]

[DOI]

Krzysztof Brzostowski

Proceedings of the Progress in Systems Engineering, 2014

Accelerated learning for Restricted Boltzmann Machine with momentum term.

[BibT_eX]

[DOI]

Proceedings of the Progress in Systems Engineering, 2014

Sparse hidden units activation in Restricted Boltzmann Machine.

[BibT_eX]

[DOI]

Proceedings of the Progress in Systems Engineering, 2014

2013

Decision rules extraction from data stream in the presence of changing context for diabetes treatment.

[BibT_eX]

[DOI]

Knowl. Inf. Syst., 2013

Prediction of breast cancer recurrence using Classification Restricted Boltzmann Machine with Dropping.

[BibT_eX]

[DOI]

CoRR, 2013

On-line bayesian context change detection in web service systems.

[BibT_eX]

[DOI]

Proceedings of the 2013 international workshop on Hot topics in cloud services, 2013

Associative Learning Using Ising-Like Model.

[BibT_eX]

[DOI]

Proceedings of the Advances in Systems Science, 2013

Manifold Regularized Particle Filter for Articulated Human Motion Tracking.

[BibT_eX]

[DOI]

Proceedings of the Advances in Systems Science, 2013

2012

Gaussian process regression as a predictive model for Quality-of-Service in Web service systems

[BibT_eX]

[DOI]

Jerzy Swiatek

Krzysztof J. Latawiec

CoRR, 2012

On-Line Change Detection for Resource Allocation in Service-Oriented Systems.

[BibT_eX]

[DOI]

Proceedings of the Technological Innovation for Value Creation, 2012

Development of Service Composition by Applying ICT Service Mapping.

[BibT_eX]

[DOI]

Katarzyna Cieslinska

Michal Pleszkun

Proceedings of the Computer Networks - 19th International Conference, 2012

A Probabilistic Approach to Structural Change Prediction in Evolving Social Networks.

[BibT_eX]

[DOI]

Krzysztof Juszczyszyn

Proceedings of the International Conference on Advances in Social Networks Analysis and Mining, 2012

2011

Context Change Detection for Resource Allocation in Service-Oriented Systems.

[BibT_eX]

[DOI]

Piotr Rygielski

Proceedings of the Knowlege-Based and Intelligent Information and Engineering Systems, 2011

Personalisation in Service-Oriented Systems Using Markov Chain Model and Bayesian Inference.

[BibT_eX]

[DOI]

Jerzy Swiatek

Proceedings of the Technological Innovation for Sustainability, 2011

2010

Service Discovery Approach Based on Rough Sets for SOA Systems.

[BibT_eX]

[DOI]

Krzysztof Brzostowski

Witold Rekuc

Janusz Sobecki

Proceedings of the Advances in Multimedia and Network Information System Technologies, 2010

Student Courses Recommendation Using Ant Colony Optimization.

[BibT_eX]

[DOI]

Janusz Sobecki