dr. Jakub Tomczak

dr.

20092019
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Research Output 2009 2019

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Article
2019

Estimating kinetic constants in the Michaelis–Menten model from one enzymatic assay using Approximate Bayesian Computation

Tomczak, J. M. & Węglarz-Tomczak, E., 1 Oct 2019, In : FEBS Letters. 593, 19, p. 2742-2750 9 p.

Research output: Contribution to JournalArticleAcademicpeer-review

Open Access
Enzyme Assays
Assays
Enzyme kinetics
Biochemistry
Kinetic parameters

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

Tomczak, J. M., Zaręba, S., Ravanbakhsh, S. & Greiner, R., 1 Oct 2019, In : Neural Processing Letters. 50, 2, p. 1401-1419 19 p.

Research output: Contribution to JournalArticleAcademicpeer-review

Open Access
Learning
Play and Playthings
Maximum likelihood
Sampling
Datasets
2018

Helix-loop-helix peptide foldamers and their use in the construction of hydrolase mimetics

Drewniak, M., Węglarz-Tomczak, E., Ożga, K., Rudzińska-Szostak, E., Macegoniuk, K., Tomczak, J. M., Bejger, M., Rypniewski, W. & Berlicki, Ł., 1 Dec 2018, In : Bioorganic Chemistry. 81, p. 356-361 6 p.

Research output: Contribution to JournalArticleAcademicpeer-review

Hydrolases
Cycloleucine
Peptides
Enzymes
Nuclear magnetic resonance spectroscopy

Interaction prediction in structure-based virtual screening using deep learning

Gonczarek, A., Tomczak, J. M., Zaręba, S., Kaczmar, J., Dąbrowski, P. & Walczak, M. J., 1 Sep 2018, In : Computers in Biology and Medicine. 100, p. 253-258 6 p.

Research output: Contribution to JournalArticleAcademicpeer-review

Benchmarking
Screening
Learning
Molecules
Peptide Mapping
2017

Learning Invariant Features Using Subspace Restricted Boltzmann Machine

Tomczak, J. M. & Gonczarek, A., 1 Feb 2017, In : Neural Processing Letters. 45, 1, p. 173-182 10 p.

Research output: Contribution to JournalArticleAcademicpeer-review

Open Access
Entropy
Learning
Experiments
Recognition (Psychology)
2016

Articulated tracking with manifold regularized particle filter

Gonczarek, A. & Tomczak, J. M., 1 Feb 2016, In : Machine Vision and Applications. 27, 2, p. 275-286 12 p.

Research output: Contribution to JournalArticleAcademicpeer-review

Open Access
Importance sampling
Sampling

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

Ziȩba, M., Tomczak, S. K. & Tomczak, J. M., 1 Oct 2016, In : Expert Systems with Applications. 58, p. 93-101 9 p.

Research output: Contribution to JournalArticleAcademicpeer-review

Higher order statistics
Decision trees
Artificial intelligence
Support vector machines
Neural networks

Learning Informative Features from Restricted Boltzmann Machines

Tomczak, J. M., 1 Dec 2016, In : Neural Processing Letters. 44, 3, p. 735-750 16 p.

Research output: Contribution to JournalArticleAcademicpeer-review

Open Access
Object recognition
Learning
Character recognition
Speech recognition
Entropy

On some properties of the low-dimensional Gumbel perturbations in the Perturb-and-MAP model

Tomczak, J. M., 1 Aug 2016, In : Statistics and Probability Letters. 115, p. 8-15 8 p.

Research output: Contribution to JournalArticleAcademicpeer-review

Gibbs Distribution
Perturbation
Model
2015

Boosted SVM with active learning strategy for imbalanced data

Zięba, M. & Tomczak, J. M., 1 Dec 2015, In : Soft Computing. 19, 12, p. 3357-3368 12 p.

Research output: Contribution to JournalArticleAcademicpeer-review

Open Access
Learning Strategies
Active Learning
Support vector machines
Support Vector Machine
Misclassification

Classification Restricted Boltzmann Machine for comprehensible credit scoring model

Tomczak, J. M. & Zie¸ba, M., 1 Jan 2015, In : Expert Systems with Applications. 42, 4, p. 1789-1796 8 p.

Research output: Contribution to JournalArticleAcademicpeer-review

Classifiers

Probabilistic combination of classification rules and its application to medical diagnosis

Tomczak, J. M. & Zięba, M., 26 Oct 2015, In : Machine Learning. 101, 1-3, p. 105-135 31 p.

Research output: Contribution to JournalArticleAcademicpeer-review

Open Access
Random variables
Labels
Decision trees
Learning algorithms
Learning systems
2014

Application of classification restricted boltzmann machine to medical domains

Tomczak, J. M., 1 Jan 2014, In : World Applied Sciences Journal. 31, 14, p. 69-75 7 p.

Research output: Contribution to JournalArticleAcademicpeer-review

Classifiers

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

Ziȩba, M., Tomczak, J. M., Lubicz, M. & Świa̧tek, J., 1 Jan 2014, In : Applied Soft Computing Journal. 14, PART A, p. 99-108 10 p.

Research output: Contribution to JournalArticleAcademicpeer-review

Medical applications
Support vector machines
Classifiers
Costs
2013

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

Tomczak, J. M. & Gonczarek, A., 1 Jan 2013, In : Knowledge and Information Systems. 34, 3, p. 521-546 26 p.

Research output: Contribution to JournalArticleAcademicpeer-review

Open Access
Medical problems
Electricity
Health
2009

Multiobjective learning of complex recurrent neural network

DrapaŁa, J., Brzostowski, K. & Tomczak, J., 1 Dec 2009, In : Systems Science. 35, 4, p. 27-37 11 p.

Research output: Contribution to JournalArticleAcademicpeer-review

Recurrent neural networks
Recurrent Neural Networks
Large scale systems
Complex Systems
Dynamic Systems