Jakub M. Tomczak

ORCID

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 88

Top Venues

CoRR

NeurIPS

ICSEng

Neural Process. Lett.

Publications

David W. Romero, Erik J. Bekkers, Jakub M. Tomczak, Mark Hoogendoorn
Wavelet Networks: Scale-Translation Equivariant Learning From Raw Time-Series. Trans. Mach. Learn. Res. 2024 (2024)
Jan P. Engelmann, Alessandro Palma, Jakub M. Tomczak, Fabian J. Theis, Francesco Paolo Casale
Mixed Models with Multiple Instance Learning. AISTATS (2024)
Haotian Chen, Anna Kuzina, Babak Esmaeili, Jakub M. Tomczak
Variational Stochastic Gradient Descent for Deep Neural Networks. CoRR (2024)
Jakub M. Tomczak
Generative AI Systems: A Systems-based Perspective on Generative AI. CoRR (2024)
Anna Kuzina, Jakub M. Tomczak
Analyzing the Posterior Collapse in Hierarchical Variational Autoencoders. CoRR (2023)
Jie Luo, Jakub M. Tomczak, Karine Miras, Ágoston E. Eiben
A comparison of controller architectures and learning mechanisms for arbitrary robot morphologies. CoRR (2023)
Jan P. Engelmann, Alessandro Palma, Jakub M. Tomczak, Fabian J. Theis, Francesco Paolo Casale
Attention-based Multi-instance Mixed Models. CoRR (2023)
Adam Izdebski, Ewelina Weglarz-Tomczak, Ewa Szczurek, Jakub M. Tomczak
De Novo Drug Design with Joint Transformers. CoRR (2023)
Kamil Deja, Tomasz Trzcinski, Jakub M. Tomczak
Learning Data Representations with Joint Diffusion Models. CoRR (2023)
Michal Zajac, Kamil Deja, Anna Kuzina, Jakub M. Tomczak, Tomasz Trzcinski, Florian Shkurti, Piotr Milos
Exploring Continual Learning of Diffusion Models. CoRR (2023)
Sharvaree P. Vadgama, Jakub M. Tomczak, Erik J. Bekkers
Continuous Kendall Shape Variational Autoencoders. GSI (1) (2023)
Jie Luo, Karine Miras, Jakub M. Tomczak, Ágoston E. Eiben
Lamarck's Revenge: Inheritance of Learned Traits Can Make Robot Evolution Better. CoRR (2023)
Kamil Deja, Tomasz Trzcinski, Jakub M. Tomczak
Learning Data Representations with Joint Diffusion Models. ECML/PKDD (2) (2023)
David M. Knigge, David W. Romero, Albert Gu, Efstratios Gavves, Erik J. Bekkers, Jakub M. Tomczak, Mark Hoogendoorn, Jan-Jakob Sonke
Modelling Long Range Dependencies in N-D: From Task-Specific to a General Purpose CNN. CoRR (2023)
Emile van Krieken, Thiviyan Thanapalasingam, Jakub M. Tomczak, Frank van Harmelen, Annette ten Teije
A-NeSI: A Scalable Approximate Method for Probabilistic Neurosymbolic Inference. NeurIPS (2023)
Gongjin Lan, Jakub M. Tomczak, Diederik M. Roijers, A. E. Eiben
Time efficiency in optimization with a bayesian-Evolutionary algorithm. Swarm Evol. Comput. 69 (2022)
Anna Kuzina, Max Welling, Jakub M. Tomczak
Alleviating Adversarial Attacks on Variational Autoencoders with MCMC. NeurIPS (2022)
Emile van Krieken, Thiviyan Thanapalasingam, Jakub M. Tomczak, Frank van Harmelen, Annette ten Teije
A-NeSI: A Scalable Approximate Method for Probabilistic Neurosymbolic Inference. CoRR (2022)
David W. Romero, David M. Knigge, Albert Gu, Erik J. Bekkers, Efstratios Gavves, Jakub M. Tomczak, Mark Hoogendoorn
Towards a General Purpose CNN for Long Range Dependencies in ND. CoRR (2022)
Anna Kuzina, Max Welling, Jakub M. Tomczak
Defending Variational Autoencoders from Adversarial Attacks with MCMC. CoRR (2022)
Kamil Deja, Anna Kuzina, Tomasz Trzcinski, Jakub M. Tomczak
On Analyzing Generative and Denoising Capabilities of Diffusion-based Deep Generative Models. NeurIPS (2022)
Jie Luo, Aart C. Stuurman, Jakub M. Tomczak, Jacintha Ellers, Ágoston E. Eiben
The Effects of Learning in Morphologically Evolving Robot Systems. Frontiers Robotics AI 9 (2022)
Kamil Deja, Anna Kuzina, Tomasz Trzcinski, Jakub M. Tomczak
On Analyzing Generative and Denoising Capabilities of Diffusion-based Deep Generative Models. CoRR (2022)
Ewelina Weglarz-Tomczak, Jakub M. Tomczak, Stanley Brul
M2R: a Python add-on to cobrapy for modifying human genome-scale metabolic reconstruction using the gut microbiota models. Bioinform. 37 (17) (2021)
Anna Kuzina, Max Welling, Jakub M. Tomczak
Diagnosing Vulnerability of Variational Auto-Encoders to Adversarial Attacks. CoRR (2021)
Yura Perugachi-Diaz, Jakub M. Tomczak, Sandjai Bhulai
Invertible DenseNets with Concatenated LipSwish. NeurIPS (2021)
Yura Perugachi-Diaz, Jakub M. Tomczak, Sandjai Bhulai
Invertible DenseNets with Concatenated LipSwish. CoRR (2021)
David W. Romero, Anna Kuzina, Erik J. Bekkers, Jakub M. Tomczak, Mark Hoogendoorn
CKConv: Continuous Kernel Convolution For Sequential Data. CoRR (2021)
David W. Romero, Robert-Jan Bruintjes, Jakub M. Tomczak, Erik J. Bekkers, Mark Hoogendoorn, Jan C. van Gemert
FlexConv: Continuous Kernel Convolutions with Differentiable Kernel Sizes. CoRR (2021)
Ilze Amanda Auzina, Jakub M. Tomczak
Approximate Bayesian Computation for Discrete Spaces. Entropy 23 (3) (2021)
Maximilian Ilse, Jakub M. Tomczak, Patrick Forré
Selecting Data Augmentation for Simulating Interventions. ICML (2021)
Gongjin Lan, Maarten van Hooft, Matteo De Carlo, Jakub M. Tomczak, A. E. Eiben
Learning locomotion skills in evolvable robots. Neurocomputing 452 (2021)
Emile van Krieken, Jakub M. Tomczak, Annette ten Teije
Storchastic: A Framework for General Stochastic Automatic Differentiation. NeurIPS (2021)
Jie Luo, Jakub M. Tomczak, Ágoston E. Eiben
The Effects of Learning in Morphologically Evolving Robot Systems. CoRR (2021)
Justus F. Hübotter, Pablo Lanillos, Jakub M. Tomczak
Training Deep Spiking Auto-encoders without Bursting or Dying Neurons through Regularization. CoRR (2021)
Yura Perugachi-Diaz, Jakub M. Tomczak, Sandjai Bhulai
Deep learning for white cabbage seedling prediction. Comput. Electron. Agric. 184 (2021)
Jie Luo, Aart Stuurman, Jakub M. Tomczak, Jacintha Ellers, Ágoston E. Eiben
The Effects of Learning in Morphologically Evolving Robot Systems. CoRR (2021)
Emile van Krieken, Jakub M. Tomczak, Annette ten Teije
Storchastic: A Framework for General Stochastic Automatic Differentiation. CoRR (2021)
Gongjin Lan, Matteo De Carlo, Fuda van Diggelen, Jakub M. Tomczak, Diederik M. Roijers, A. E. Eiben
Learning directed locomotion in modular robots with evolvable morphologies. Appl. Soft Comput. 111 (2021)
Ioannis Gatopoulos, Jakub M. Tomczak
Self-Supervised Variational Auto-Encoders. Entropy 23 (6) (2021)
David W. Romero, Erik J. Bekkers, Jakub M. Tomczak, Mark Hoogendoorn
Attentive Group Equivariant Convolutional Networks. ICML (2020)
Ioannis Gatopoulos, Romain Lepert, Auke Wiggers, Giovanni Mariani, Jakub M. Tomczak
Evolutionary Algorithm with Non-parametric Surrogate Model for Tensor Program optimization. CEC (2020)
Gongjin Lan, Jakub M. Tomczak, Diederik M. Roijers, A. E. Eiben
Time Efficiency in Optimization with a Bayesian-Evolutionary Algorithm. CoRR (2020)
Emiel Hoogeboom, Victor Garcia Satorras, Jakub M. Tomczak, Max Welling
The Convolution Exponential and Generalized Sylvester Flows. NeurIPS (2020)
Jakub M. Tomczak, Ewelina Weglarz-Tomczak, Ágoston E. Eiben
Differential Evolution with Reversible Linear Transformations. GECCO Companion (2020)
Maximilian Ilse, Jakub M. Tomczak, Christos Louizos, Max Welling
DIVA: Domain Invariant Variational Autoencoders. MIDL (2020)
Alessandro Zonta, Ali El Hassouni, David W. Romero, Jakub M. Tomczak
Generative Fourier-Based Auto-encoders: Preliminary Results. LOD (2) (2020)
Jakub M. Tomczak
General Invertible Transformations for Flow-based Generative Modeling. CoRR (2020)
Ilze Amanda Auzina, Jakub M. Tomczak
ABC-Di: Approximate Bayesian Computation for Discrete Data. CoRR (2020)
Ioannis Gatopoulos, Jakub M. Tomczak
Self-Supervised Variational Auto-Encoders. CoRR (2020)
Jakub M. Tomczak, Ewelina Weglarz-Tomczak, Ágoston E. Eiben
Differential Evolution with Reversible Linear Transformations. CoRR (2020)
David W. Romero, Erik J. Bekkers, Jakub M. Tomczak, Mark Hoogendoorn
Wavelet Networks: Scale Equivariant Learning From Raw Waveforms. CoRR (2020)
Emiel Hoogeboom, Victor Garcia Satorras, Jakub M. Tomczak, Max Welling
The Convolution Exponential and Generalized Sylvester Flows. CoRR (2020)
Emiel Hoogeboom, Taco S. Cohen, Jakub M. Tomczak
Learning Discrete Distributions by Dequantization. CoRR (2020)
Ewelina Weglarz-Tomczak, Jakub M. Tomczak, Ágoston E. Eiben, Stanley Brul
Population-based Optimization for Kinetic Parameter Identification in Glycolytic Pathway in Saccharomyces cerevisiae. CoRR (2020)
Maximilian Ilse, Jakub M. Tomczak, Patrick Forré
Designing Data Augmentation for Simulating Interventions. CoRR (2020)
Ioannis Gatopoulos, Maarten Stol, Jakub M. Tomczak
Super-resolution Variational Auto-Encoders. CoRR (2020)
Gongjin Lan, Maarten van Hooft, Matteo De Carlo, Jakub M. Tomczak, A. E. Eiben
Learning Locomotion Skills in Evolvable Robots. CoRR (2020)
Yura Perugachi-Diaz, Jakub M. Tomczak, Sandjai Bhulai
i-DenseNets. CoRR (2020)
Gongjin Lan, Matteo De Carlo, Fuda van Diggelen, Jakub M. Tomczak, Diederik M. Roijers, A. E. Eiben
Learning Directed Locomotion in Modular Robots with Evolvable Morphologies. CoRR (2020)
David W. Romero, Erik J. Bekkers, Jakub M. Tomczak, Mark Hoogendoorn
Attentive Group Equivariant Convolutional Networks. CoRR (2020)
AmirHossein Habibian, Ties van Rozendaal, Jakub M. Tomczak, Taco S. Cohen
Video Compression With Rate-Distortion Autoencoders. CoRR (2019)
ChangYong Oh, Jakub M. Tomczak, Efstratios Gavves, Max Welling
Combinatorial Bayesian Optimization using the Graph Cartesian Product. NeurIPS (2019)
Tim R. Davidson, Jakub M. Tomczak, Efstratios Gavves
Increasing Expressivity of a Hyperspherical VAE. CoRR (2019)
ChangYong Oh, Jakub M. Tomczak, Efstratios Gavves, Max Welling
Combinatorial Bayesian Optimization using Graph Representations. CoRR (2019)
Jakub M. Tomczak, Romain Lepert, Auke Wiggers
Simulating Execution Time of Tensor Programs using Graph Neural Networks. CoRR (2019)
Maximilian Ilse, Jakub M. Tomczak, Christos Louizos, Max Welling
DIVA: Domain Invariant Variational Autoencoders. CoRR (2019)
Maximilian Ilse, Jakub M. Tomczak, Christos Louizos, Max Welling
DIVA: Domain Invariant Variational Autoencoder. DGS@ICLR (2019)
Jakub M. Tomczak, Szymon Zareba, Siamak Ravanbakhsh, Russell Greiner
Low-Dimensional Perturb-and-MAP Approach for Learning Restricted Boltzmann Machines. Neural Process. Lett. 50 (2) (2019)
AmirHossein Habibian, Ties van Rozendaal, Jakub M. Tomczak, Taco Cohen
Video Compression With Rate-Distortion Autoencoders. ICCV (2019)
Tim R. Davidson, Luca Falorsi, Nicola De Cao, Thomas Kipf, Jakub M. Tomczak
Hyperspherical Variational Auto-Encoders. CoRR (2018)
Philip Botros, Jakub M. Tomczak
Hierarchical VampPrior Variational Fair Auto-Encoder. CoRR (2018)
Rianne van den Berg, Leonard Hasenclever, Jakub M. Tomczak, Max Welling
Sylvester Normalizing Flows for Variational Inference. CoRR (2018)
Tim R. Davidson, Luca Falorsi, Nicola De Cao, Thomas Kipf, Jakub M. Tomczak
Hyperspherical Variational Auto-Encoders. UAI (2018)
Adam Gonczarek, Jakub M. Tomczak, Szymon Zareba, Joanna Kaczmar, Piotr Dabrowski, Michal J. Walczak
Interaction prediction in structure-based virtual screening using deep learning. Comput. Biol. Medicine 100 (2018)
Maximilian Ilse, Jakub M. Tomczak, Max Welling
Attention-based Deep Multiple Instance Learning. ICML (2018)
Maximilian Ilse, Jakub M. Tomczak, Max Welling
Attention-based Deep Multiple Instance Learning. CoRR (2018)
Rianne van den Berg, Leonard Hasenclever, Jakub M. Tomczak, Max Welling
Sylvester Normalizing Flows for Variational Inference. UAI (2018)
Jakub M. Tomczak, Max Welling
VAE with a VampPrior. AISTATS (2018)
Jakub M. Tomczak, Maximilian Ilse, Max Welling
Deep Learning with Permutation-invariant Operator for Multi-instance Histopathology Classification. CoRR (2017)
Jakub M. Tomczak, Adam Gonczarek
Learning Invariant Features Using Subspace Restricted Boltzmann Machine. Neural Process. Lett. 45 (1) (2017)
Jakub M. Tomczak, Max Welling
VAE with a VampPrior. CoRR (2017)
Jakub M. Tomczak, Max Welling
Improving Variational Auto-Encoders using Householder Flow. CoRR (2016)
Jakub M. Tomczak
Learning Informative Features from Restricted Boltzmann Machines. Neural Process. Lett. 44 (3) (2016)
Maciej Zieba, Sebastian K. Tomczak, Jakub M. Tomczak
Ensemble boosted trees with synthetic features generation in application to bankruptcy prediction. Expert Syst. Appl. 58 (2016)
Adam Gonczarek, Jakub M. Tomczak, Szymon Zareba, Joanna Kaczmar, Piotr Dabrowski, Michal J. Walczak
Learning Deep Architectures for Interaction Prediction in Structure-based Virtual Screening. CoRR (2016)
Adam Gonczarek, Jakub M. Tomczak
Articulated tracking with manifold regularized particle filter. Mach. Vis. Appl. 27 (2) (2016)
Maciej Zieba, Jakub M. Tomczak, Jerzy Swiatek
Self-paced Learning for Imbalanced Data. ACIIDS (1) (2016)
Jakub M. Tomczak, Maciej Zieba
Probabilistic combination of classification rules and its application to medical diagnosis. Mach. Learn. 101 (1-3) (2015)
Maciej Zieba, Jakub M. Tomczak
Boosted SVM with active learning strategy for imbalanced data. Soft Comput. 19 (12) (2015)
Jakub M. Tomczak, Maciej Zieba
Classification Restricted Boltzmann Machine for comprehensible credit scoring model. Expert Syst. Appl. 42 (4) (2015)
Maciej Zieba, Jakub M. Tomczak, Adam Gonczarek
RBM-SMOTE: Restricted Boltzmann Machines for Synthetic Minority Oversampling Technique. ACIIDS (1) (2015)
Szymon Zareba, Adam Gonczarek, Jakub M. Tomczak, Jerzy Swiatek
Accelerated learning for Restricted Boltzmann Machine with momentum term. ICSEng (2014)
Jakub M. Tomczak, Adam Gonczarek
Sparse hidden units activation in Restricted Boltzmann Machine. ICSEng (2014)
Maciej Zieba, Jakub M. Tomczak, Krzysztof Brzostowski
Selecting right questions with Restricted Boltzmann Machines. ICSEng (2014)
Maciej Zieba, Jakub M. Tomczak, Marek Lubicz, Jerzy Swiatek
Boosted SVM for extracting rules from imbalanced data in application to prediction of the post-operative life expectancy in the lung cancer patients. Appl. Soft Comput. 14 (2014)
Jakub M. Tomczak, Adam Gonczarek
Subspace Restricted Boltzmann Machine. CoRR (2014)
Jakub M. Tomczak
Associative Learning Using Ising-Like Model. ICSS (2013)
Jakub M. Tomczak
Prediction of breast cancer recurrence using Classification Restricted Boltzmann Machine with Dropping. CoRR (2013)
Adam Gonczarek, Jakub M. Tomczak
Manifold Regularized Particle Filter for Articulated Human Motion Tracking. ICSS (2013)

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Publication Activity (10 Years)

Top Topics

Top Venues

Jakub M. Tomczak