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Przemyslaw Biecek
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- affiliation: Warsaw University of Technology, Poland
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2020 – today
- 2024
- [j30]André Fonseca, Mikolaj Spytek, Przemyslaw Biecek, Clara Cordeiro
, Nuno Sepúlveda:
Antibody selection strategies and their impact in predicting clinical malaria based on multi-sera data. BioData Min. 17(1) (2024) - [j29]Hubert Baniecki, Przemyslaw Biecek
:
Adversarial attacks and defenses in explainable artificial intelligence: A survey. Inf. Fusion 107: 102303 (2024) - [j28]Weronika Hryniewska
, Adrianna Grudzien, Przemyslaw Biecek:
LIMEcraft: handcrafted superpixel selection and inspection for Visual eXplanations. Mach. Learn. 113(5): 3143-3160 (2024) - [j27]Katarzyna Woznica
, Mateusz Grzyb, Zuzanna Trafas, Przemyslaw Biecek:
Consolidated learning: a domain-specific model-free optimization strategy with validation on metaMIMIC benchmarks. Mach. Learn. 113(7): 4925-4949 (2024) - [c22]Avigyan Bhattacharya
, Tapabrata Chakraborti
, Subhadip Basu
, Alistair Knott
, Dino Pedreschi
, Raja G. Chatila
, Susan Leavy
, David M. Eyers
, Paul D. Teal
, Przemyslaw Biecek
:
Towards a crowdsourced framework for online hate speech moderation - a case study in the Indian political scenario. WebSci (Companion) 2024: 75-84 - [e7]Slawomir Nowaczyk
, Przemyslaw Biecek
, Neo Christopher Chung
, Mauro Vallati, Pawel Skruch
, Joanna Jaworek-Korjakowska
, Simon Parkinson, Alexandros Nikitas, Martin Atzmüller, Tomás Kliegr
, Ute Schmid, Szymon Bobek
, Nada Lavrac, Marieke Peeters, Roland van Dierendonck, Saskia Robben, Eunika Mercier-Laurent, Gülgün Kayakutlu
, Mieczyslaw Lech Owoc
, Karl Mason, Abdul Wahid, Pierangela Bruno, Francesco Calimeri
, Francesco Cauteruccio, Giorgio Terracina, Diedrich Wolter
, Jochen L. Leidner, Michael Kohlhase, Vania Dimitrova
:
Artificial Intelligence. ECAI 2023 International Workshops - XAI³, TACTIFUL, XI-ML, SEDAMI, RAAIT, AI4S, HYDRA, AI4AI, Kraków, Poland, September 30 - October 4, 2023, Proceedings, Part I. Communications in Computer and Information Science 1947, Springer 2024, ISBN 978-3-031-50395-5 [contents] - [e6]Slawomir Nowaczyk
, Przemyslaw Biecek
, Neo Christopher Chung
, Mauro Vallati, Pawel Skruch
, Joanna Jaworek-Korjakowska
, Simon Parkinson, Alexandros Nikitas, Martin Atzmüller, Tomás Kliegr
, Ute Schmid, Szymon Bobek
, Nada Lavrac, Marieke Peeters, Roland van Dierendonck, Saskia Robben, Eunika Mercier-Laurent, Gülgün Kayakutlu
, Mieczyslaw Lech Owoc
, Karl Mason, Abdul Wahid, Pierangela Bruno, Francesco Calimeri
, Francesco Cauteruccio, Giorgio Terracina, Diedrich Wolter
, Jochen L. Leidner, Michael Kohlhase, Vania Dimitrova
:
Artificial Intelligence. ECAI 2023 International Workshops - XAI³, TACTIFUL, XI-ML, SEDAMI, RAAIT, AI4S, HYDRA, AI4AI, Kraków, Poland, September 30 - October 4, 2023, Proceedings, Part II. Communications in Computer and Information Science 1948, Springer 2024, ISBN 978-3-031-50484-6 [contents] - [i73]Paulina Tomaszewska, Elzbieta Sienkiewicz, Mai P. Hoang, Przemyslaw Biecek:
Deep spatial context: when attention-based models meet spatial regression. CoRR abs/2401.10044 (2024) - [i72]Weronika Hryniewska-Guzik, Bartosz Sawicki, Przemyslaw Biecek:
NormEnsembleXAI: Unveiling the Strengths and Weaknesses of XAI Ensemble Techniques. CoRR abs/2401.17200 (2024) - [i71]Przemyslaw Bombinski, Patryk Szatkowski, Bartlomiej Sobieski, Tymoteusz Kwiecinski, Szymon Plotka, Mariusz Adamek, Marcin Banasiuk, Mariusz I. Furmanek, Przemyslaw Biecek:
Underestimation of lung regions on chest X-ray segmentation masks assessed by comparison with total lung volume evaluated on computed tomography. CoRR abs/2402.11510 (2024) - [i70]Przemyslaw Biecek, Wojciech Samek:
Explain to Question not to Justify. CoRR abs/2402.13914 (2024) - [i69]Vladimir Zaigrajew, Hubert Baniecki, Lukasz Tulczyjew, Agata M. Wijata, Jakub Nalepa, Nicolas Longépé, Przemyslaw Biecek:
Red Teaming Models for Hyperspectral Image Analysis Using Explainable AI. CoRR abs/2403.08017 (2024) - [i68]Sophie Hanna Langbein, Mateusz Krzyzinski, Mikolaj Spytek, Hubert Baniecki, Przemyslaw Biecek, Marvin N. Wright:
Interpretable Machine Learning for Survival Analysis. CoRR abs/2403.10250 (2024) - [i67]Krzysztof Jankowski, Bartlomiej Sobieski, Mateusz Kwiatkowski, Jakub Szulc, Michal Janik, Hubert Baniecki, Przemyslaw Biecek:
Red-Teaming Segment Anything Model. CoRR abs/2404.02067 (2024) - [i66]Weronika Hryniewska-Guzik, Jakub Bilski, Bartosz Chrostowski, Jakub Drak Sbahi, Przemyslaw Biecek:
A comparative analysis of deep learning models for lung segmentation on X-ray images. CoRR abs/2404.06455 (2024) - [i65]Weronika Hryniewska-Guzik, Luca Longo, Przemyslaw Biecek:
CNN-based explanation ensembling for dataset, representation and explanations evaluation. CoRR abs/2404.10387 (2024) - [i64]Bartlomiej Sobieski, Przemyslaw Biecek:
Global Counterfactual Directions. CoRR abs/2404.12488 (2024) - [i63]Piotr Wilczynski, Wiktoria Mieleszczenko-Kowszewicz, Przemyslaw Biecek:
Resistance Against Manipulative AI: key factors and possible actions. CoRR abs/2404.14230 (2024) - [i62]Paulina Tomaszewska, Przemyslaw Biecek:
Position paper: Do not explain (vision models) without context. CoRR abs/2404.18316 (2024) - [i61]Mustafa Cavus, Przemyslaw Biecek:
An Experimental Study on the Rashomon Effect of Balancing Methods in Imbalanced Classification. CoRR abs/2405.01557 (2024) - [i60]Paulina Tomaszewska, Mateusz Sperkowski, Przemyslaw Biecek:
Does context matter in digital pathology? CoRR abs/2405.14301 (2024) - [i59]Hubert Baniecki, Giuseppe Casalicchio, Bernd Bischl, Przemyslaw Biecek:
On the Robustness of Global Feature Effect Explanations. CoRR abs/2406.09069 (2024) - [i58]Hubert Baniecki, Giuseppe Casalicchio, Bernd Bischl, Przemyslaw Biecek:
Efficient and Accurate Explanation Estimation with Distribution Compression. CoRR abs/2406.18334 (2024) - [i57]Szymon Plotka, Maciej Chrabaszcz, Przemyslaw Biecek:
Swin SMT: Global Sequential Modeling in 3D Medical Image Segmentation. CoRR abs/2407.07514 (2024) - [i56]Maciej Chrabaszcz, Hubert Baniecki, Piotr Komorowski, Szymon Plotka, Przemyslaw Biecek:
Aggregated Attributions for Explanatory Analysis of 3D Segmentation Models. CoRR abs/2407.16653 (2024) - 2023
- [j26]Mikolaj Spytek, Mateusz Krzyzinski
, Sophie Hanna Langbein, Hubert Baniecki, Marvin N. Wright, Przemyslaw Biecek
:
survex: an R package for explaining machine learning survival models. Bioinform. 39(12) (2023) - [j25]Alistair Knott
, Dino Pedreschi, Raja Chatila, Tapabrata Chakraborti, Susan Leavy
, Ricardo Baeza-Yates, David M. Eyers, Andrew Trotman, Paul D. Teal, Przemyslaw Biecek, Stuart Russell, Yoshua Bengio:
Generative AI models should include detection mechanisms as a condition for public release. Ethics Inf. Technol. 25(4): 55 (2023) - [j24]Mateusz Krzyzinski
, Mikolaj Spytek
, Hubert Baniecki
, Przemyslaw Biecek
:
SurvSHAP(t): Time-dependent explanations of machine learning survival models. Knowl. Based Syst. 262: 110234 (2023) - [c21]Hubert Baniecki
, Bartlomiej Sobieski, Przemyslaw Bombinski, Patryk Szatkowski, Przemyslaw Biecek
:
Hospital Length of Stay Prediction Based on Multi-modal Data Towards Trustworthy Human-AI Collaboration in Radiomics. AIME 2023: 65-74 - [c20]Piotr Komorowski, Hubert Baniecki, Przemyslaw Biecek:
Towards Evaluating Explanations of Vision Transformers for Medical Imaging. CVPR Workshops 2023: 3726-3732 - [c19]Adrian Stando, Mustafa Cavus, Przemyslaw Biecek:
The Effect of Balancing Methods on Model Behavior in Imbalanced Classification Problems. LIDTA 2023: 16-30 - [e5]Irena Koprinska
, Paolo Mignone, Riccardo Guidotti
, Szymon Jaroszewicz, Holger Fröning
, Francesco Gullo, Pedro M. Ferreira
, Damian Roqueiro, Gaia Ceddia, Slawomir Nowaczyk
, João Gama
, Rita P. Ribeiro, Ricard Gavaldà
, Elio Masciari
, Zbigniew W. Ras
, Ettore Ritacco, Francesca Naretto, Andreas Theissler, Przemyslaw Biecek
, Wouter Verbeke
, Gregor Schiele
, Franz Pernkopf
, Michaela Blott, Ilaria Bordino, Ivan Luciano Danesi, Giovanni Ponti, Lorenzo Severini, Annalisa Appice
, Giuseppina Andresini
, Ibéria Medeiros, Guilherme Graça
, Lee A. D. Cooper
, Naghmeh Ghazaleh
, Jonas Richiardi
, Diego Saldana Miranda, Konstantinos Sechidis
, Arif Canakoglu, Sara Pidò, Pietro Pinoli, Albert Bifet
, Sepideh Pashami
:
Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part I. Communications in Computer and Information Science 1752, Springer 2023, ISBN 978-3-031-23617-4 [contents] - [e4]Irena Koprinska
, Paolo Mignone, Riccardo Guidotti
, Szymon Jaroszewicz, Holger Fröning
, Francesco Gullo, Pedro M. Ferreira
, Damian Roqueiro, Gaia Ceddia, Slawomir Nowaczyk
, João Gama
, Rita P. Ribeiro, Ricard Gavaldà
, Elio Masciari
, Zbigniew W. Ras
, Ettore Ritacco, Francesca Naretto, Andreas Theissler, Przemyslaw Biecek
, Wouter Verbeke, Gregor Schiele
, Franz Pernkopf
, Michaela Blott, Ilaria Bordino, Ivan Luciano Danesi, Giovanni Ponti, Lorenzo Severini, Annalisa Appice
, Giuseppina Andresini
, Ibéria Medeiros, Guilherme Graça
, Lee A. D. Cooper
, Naghmeh Ghazaleh
, Jonas Richiardi
, Diego Saldana Miranda, Konstantinos Sechidis
, Arif Canakoglu, Sara Pidò, Pietro Pinoli, Albert Bifet
, Sepideh Pashami
:
Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part II. Communications in Computer and Information Science 1753, Springer 2023, ISBN 978-3-031-23632-7 [contents] - [i55]Piotr Wilczynski, Artur Zólkowski, Mateusz Krzyzinski, Emilia Wisnios, Bartosz Pielinski, Stanislaw Gizinski, Julian Sienkiewicz, Przemyslaw Biecek:
HADES: Homologous Automated Document Exploration and Summarization. CoRR abs/2302.13099 (2023) - [i54]Przemyslaw Biecek, Hubert Baniecki, Mateusz Krzyzinski:
Performance is not enough: a story of the Rashomon's quartet. CoRR abs/2302.13356 (2023) - [i53]Mikolaj Spytek, Weronika Hryniewska-Guzik, Jaroslaw Zygierewicz
, Jacek Rogala, Przemyslaw Biecek:
Challenges facing the explainability of age prediction models: case study for two modalities. CoRR abs/2303.06640 (2023) - [i52]Hubert Baniecki, Bartlomiej Sobieski, Przemyslaw Bombinski, Patryk Szatkowski, Przemyslaw Biecek:
Hospital Length of Stay Prediction Based on Multi-modal Data towards Trustworthy Human-AI Collaboration in Radiomics. CoRR abs/2303.09817 (2023) - [i51]Piotr Komorowski, Hubert Baniecki, Przemyslaw Biecek:
Towards Evaluating Explanations of Vision Transformers for Medical Imaging. CoRR abs/2304.06133 (2023) - [i50]Weronika Hryniewska, Piotr Czarnecki, Jakub Wisniewski, Przemyslaw Bombinski, Przemyslaw Biecek:
Prevention is better than cure: a case study of the abnormalities detection in the chest. CoRR abs/2305.10961 (2023) - [i49]Hubert Baniecki, Przemyslaw Biecek:
Adversarial Attacks and Defenses in Explainable Artificial Intelligence: A Survey. CoRR abs/2306.06123 (2023) - [i48]Katarzyna Woznica, Piotr Wilczynski, Przemyslaw Biecek:
SeFNet: Bridging Tabular Datasets with Semantic Feature Nets. CoRR abs/2306.11636 (2023) - [i47]Adrian Stando, Mustafa Cavus, Przemyslaw Biecek:
The Effect of Balancing Methods on Model Behavior in Imbalanced Classification Problems. CoRR abs/2307.00157 (2023) - [i46]Bastian Pfeifer, Mateusz Krzyzinski, Hubert Baniecki, Anna Saranti, Andreas Holzinger, Przemyslaw Biecek:
Explainable AI with counterfactual paths. CoRR abs/2307.07764 (2023) - [i45]Weronika Hryniewska-Guzik, Maria Kedzierska, Przemyslaw Biecek:
Multi-task learning for classification, segmentation, reconstruction, and detection on chest CT scans. CoRR abs/2308.01137 (2023) - [i44]Katarzyna Kobylinska, Mateusz Krzyzinski, Rafal Machowicz, Mariusz Adamek, Przemyslaw Biecek:
Exploration of Rashomon Set Assists Explanations for Medical Data. CoRR abs/2308.11446 (2023) - [i43]Mustafa Cavus, Adrian Stando, Przemyslaw Biecek:
Glocal Explanations of Expected Goal Models in Soccer. CoRR abs/2308.15559 (2023) - [i42]Mikolaj Spytek, Mateusz Krzyzinski, Sophie Hanna Langbein, Hubert Baniecki, Marvin N. Wright, Przemyslaw Biecek:
survex: an R package for explaining machine learning survival models. CoRR abs/2308.16113 (2023) - [i41]Hubert Baniecki, Maciej Chrabaszcz, Andreas Holzinger, Bastian Pfeifer, Anna Saranti, Przemyslaw Biecek:
Be Careful When Evaluating Explanations Regarding Ground Truth. CoRR abs/2311.04813 (2023) - [i40]Stanislaw Gizinski, Paulina Kaczynska, Hubert Ruczynski, Emilia Wisnios, Bartosz Pielinski, Przemyslaw Biecek, Julian Sienkiewicz:
Big Tech influence over AI research revisited: memetic analysis of attribution of ideas to affiliation. CoRR abs/2312.12881 (2023) - 2022
- [j23]Angela Lombardi, Domenico Diacono, Nicola Amoroso, Przemyslaw Biecek, Alfonso Monaco, Loredana Bellantuono
, Ester Pantaleo, Giancarlo Logroscino
, Roberto De Blasi, Sabina Tangaro
, Roberto Bellotti:
A robust framework to investigate the reliability and stability of explainable artificial intelligence markers of Mild Cognitive Impairment and Alzheimer's Disease. Brain Informatics 9(1): 17 (2022) - [j22]Michael Bücker
, Gero Szepannek
, Alicja Gosiewska
, Przemyslaw Biecek
:
Transparency, auditability, and explainability of machine learning models in credit scoring. J. Oper. Res. Soc. 73(1): 70-90 (2022) - [j21]Alicja Gosiewska
, Katarzyna Woznica
, Przemyslaw Biecek:
Interpretable meta-score for model performance. Nat. Mac. Intell. 4(9): 792-800 (2022) - [j20]Jakub Wisniewski, Przemyslaw Biecek:
fairmodels: a Flexible Tool for Bias Detection, Visualization, and Mitigation in Binary Classification Models. R J. 14(1): 227-243 (2022) - [c18]Hubert Baniecki, Przemyslaw Biecek:
Manipulating SHAP via Adversarial Data Perturbations (Student Abstract). AAAI 2022: 12907-12908 - [c17]Mustafa Cavus, Przemyslaw Biecek:
Explainable expected goal models for performance analysis in football analytics. DSAA 2022: 1-9 - [c16]Alicja Gosiewska, Katarzyna Woznica, Przemyslaw Biecek:
Interpretable Meta-Score for Model Performance: Extended Abstract. Meta-Knowledge Transfer @ ECML/PKDD 2022: 75-77 - [c15]Hubert Baniecki, Wojciech Kretowicz, Przemyslaw Biecek:
Fooling Partial Dependence via Data Poisoning. ECML/PKDD (3) 2022: 121-136 - [i39]Katarzyna Woznica, Mateusz Grzyb, Zuzanna Trafas, Przemyslaw Biecek:
Consolidated learning - a domain-specific model-free optimization strategy with examples for XGBoost and MIMIC-IV. CoRR abs/2201.11815 (2022) - [i38]Mustafa Cavus, Przemyslaw Biecek:
Explainable expected goal models for performance analysis in football analytics. CoRR abs/2206.07212 (2022) - [i37]Przemyslaw Biecek:
Performance, Opaqueness, Consequences, and Assumptions: Simple questions for responsible planning of machine learning solutions. CoRR abs/2208.09966 (2022) - [i36]Mateusz Krzyzinski, Mikolaj Spytek, Hubert Baniecki, Przemyslaw Biecek:
SurvSHAP(t): Time-dependent explanations of machine learning survival models. CoRR abs/2208.11080 (2022) - [i35]Artur Zólkowski, Mateusz Krzyzinski, Piotr Wilczynski, Stanislaw Gizinski, Emilia Wisnios, Bartosz Pielinski, Julian Sienkiewicz, Przemyslaw Biecek:
Climate Policy Tracker: Pipeline for automated analysis of public climate policies. CoRR abs/2211.05852 (2022) - 2021
- [j19]Alicja Gosiewska
, Anna Kozak
, Przemyslaw Biecek:
Simpler is better: Lifting interpretability-performance trade-off via automated feature engineering. Decis. Support Syst. 150: 113556 (2021) - [j18]Adam Gabriel Dobrakowski
, Agnieszka Mykowiecka, Malgorzata Marciniak, Wojciech Jaworski, Przemyslaw Biecek:
Interpretable segmentation of medical free-text records based on word embeddings. J. Intell. Inf. Syst. 57(3): 447-465 (2021) - [j17]Hubert Baniecki, Wojciech Kretowicz, Piotr Piatyszek, Jakub Wisniewski, Przemyslaw Biecek:
dalex: Responsible Machine Learning with Interactive Explainability and Fairness in Python. J. Mach. Learn. Res. 22: 214:1-214:7 (2021) - [j16]Weronika Hryniewska
, Przemyslaw Bombinski, Patryk Szatkowski, Paulina Tomaszewska
, Artur Przelaskowski
, Przemyslaw Biecek
:
Checklist for responsible deep learning modeling of medical images based on COVID-19 detection studies. Pattern Recognit. 118: 108035 (2021) - [c14]Hubert Baniecki, Przemyslaw Biecek:
Responsible Prediction Making of COVID-19 Mortality (Student Abstract). AAAI 2021: 15755-15756 - [c13]Tomasz Stanislawek
, Filip Gralinski
, Anna Wróblewska
, Dawid Lipinski
, Agnieszka Kaliska
, Paulina Rosalska
, Bartosz Topolski
, Przemyslaw Biecek
:
Kleister: Key Information Extraction Datasets Involving Long Documents with Complex Layouts. ICDAR (1) 2021: 564-579 - [c12]Barbara Rychalska, Piotr Babel, Konrad Goluchowski, Andrzej Michalowski, Jacek Dabrowski, Przemyslaw Biecek:
Cleora: A Simple, Strong and Scalable Graph Embedding Scheme. ICONIP (4) 2021: 338-352 - [c11]Wojciech Jaworski, Przemyslaw Biecek, Adam Gabriel Dobrakowski, Malgorzata Marciniak, Agnieszka Mykowiecka, Agnieszka Morusiewicz, Joanna Przetacka, Lukasz Kaminski:
Supporting Doctor's Decisions Based on Electronic Medical Documentation in Polish. MedInfo 2021: 1076-1077 - [c10]Katarzyna Woznica
, Przemyslaw Biecek
:
Towards Explainable Meta-learning. PKDD/ECML Workshops (1) 2021: 505-520 - [e3]Michael Kamp
, Irena Koprinska
, Adrien Bibal
, Tassadit Bouadi
, Benoît Frénay
, Luis Galárraga
, José Oramas
, Linara Adilova, Yamuna Krishnamurthy
, Bo Kang
, Christine Largeron, Jefrey Lijffijt
, Tiphaine Viard, Pascal Welke
, Massimiliano Ruocco, Erlend Aune, Claudio Gallicchio, Gregor Schiele
, Franz Pernkopf
, Michaela Blott
, Holger Fröning
, Günther Schindler, Riccardo Guidotti
, Anna Monreale
, Salvatore Rinzivillo
, Przemyslaw Biecek
, Eirini Ntoutsi
, Mykola Pechenizkiy
, Bodo Rosenhahn
, Christopher L. Buckley
, Daniela Cialfi
, Pablo Lanillos
, Maxwell Ramstead
, Tim Verbelen
, Pedro M. Ferreira
, Giuseppina Andresini
, Donato Malerba
, Ibéria Medeiros
, Philippe Fournier-Viger
, M. Saqib Nawaz
, Sebastián Ventura
, Meng Sun
, Min Zhou, Valerio Bitetta, Ilaria Bordino, Andrea Ferretti, Francesco Gullo
, Giovanni Ponti, Lorenzo Severini, Rita P. Ribeiro, João Gama
, Ricard Gavaldà
, Lee A. D. Cooper
, Naghmeh Ghazaleh
, Jonas Richiardi
, Damian Roqueiro
, Diego Saldana Miranda
, Konstantinos Sechidis
, Guilherme Graça
:
Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2021, Virtual Event, September 13-17, 2021, Proceedings, Part I. Communications in Computer and Information Science 1524, Springer 2021, ISBN 978-3-030-93735-5 [contents] - [e2]Michael Kamp
, Irena Koprinska
, Adrien Bibal
, Tassadit Bouadi
, Benoît Frénay
, Luis Galárraga
, José Oramas
, Linara Adilova, Yamuna Krishnamurthy
, Bo Kang
, Christine Largeron, Jefrey Lijffijt
, Tiphaine Viard, Pascal Welke
, Massimiliano Ruocco, Erlend Aune, Claudio Gallicchio, Gregor Schiele
, Franz Pernkopf
, Michaela Blott
, Holger Fröning
, Günther Schindler, Riccardo Guidotti
, Anna Monreale
, Salvatore Rinzivillo
, Przemyslaw Biecek
, Eirini Ntoutsi
, Mykola Pechenizkiy
, Bodo Rosenhahn
, Christopher L. Buckley
, Daniela Cialfi
, Pablo Lanillos
, Maxwell Ramstead
, Tim Verbelen
, Pedro M. Ferreira
, Giuseppina Andresini
, Donato Malerba
, Ibéria Medeiros
, Philippe Fournier-Viger
, M. Saqib Nawaz
, Sebastián Ventura
, Meng Sun
, Min Zhou, Valerio Bitetta, Ilaria Bordino, Andrea Ferretti, Francesco Gullo
, Giovanni Ponti, Lorenzo Severini, Rita P. Ribeiro, João Gama
, Ricard Gavaldà
, Lee A. D. Cooper
, Naghmeh Ghazaleh
, Jonas Richiardi
, Damian Roqueiro
, Diego Saldana Miranda
, Konstantinos Sechidis
, Guilherme Graça
:
Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2021, Virtual Event, September 13-17, 2021, Proceedings, Part II. Communications in Computer and Information Science 1525, Springer 2021, ISBN 978-3-030-93732-4 [contents] - [i34]Jakub Wisniewski, Przemyslaw Biecek:
fairmodels: A Flexible Tool For Bias Detection, Visualization, And Mitigation. CoRR abs/2104.00507 (2021) - [i33]Katarzyna Pekala, Katarzyna Woznica, Przemyslaw Biecek:
Triplot: model agnostic measures and visualisations for variable importance in predictive models that take into account the hierarchical correlation structure. CoRR abs/2104.03403 (2021) - [i32]Przemyslaw Biecek, Marcin Chlebus, Janusz Gajda, Alicja Gosiewska, Anna Kozak, Dominik Ogonowski, Jakub Sztachelski, Piotr Wojewnik:
Enabling Machine Learning Algorithms for Credit Scoring - Explainable Artificial Intelligence (XAI) methods for clear understanding complex predictive models. CoRR abs/2104.06735 (2021) - [i31]Tomasz Stanislawek, Filip Gralinski, Anna Wróblewska, Dawid Lipinski, Agnieszka Kaliska, Paulina Rosalska, Bartosz Topolski, Przemyslaw Biecek:
Kleister: Key Information Extraction Datasets Involving Long Documents with Complex Layouts. CoRR abs/2105.05796 (2021) - [i30]Hubert Baniecki, Wojciech Kretowicz, Przemyslaw Biecek:
Fooling Partial Dependence via Data Poisoning. CoRR abs/2105.12837 (2021) - [i29]Katarzyna Woznica, Katarzyna Pekala, Hubert Baniecki, Wojciech Kretowicz, Elzbieta Sienkiewicz, Przemyslaw Biecek:
Do not explain without context: addressing the blind spot of model explanations. CoRR abs/2105.13787 (2021) - [i28]Stanislaw Gizinski, Michal Kuzba, Bartosz Pielinski, Julian Sienkiewicz, Stanislaw Laniewski, Przemyslaw Biecek:
MAIR: Framework for mining relationships between research articles, strategies, and regulations in the field of explainable artificial intelligence. CoRR abs/2108.06216 (2021) - [i27]Weronika Hryniewska, Adrianna Grudzien, Przemyslaw Biecek:
LIMEcraft: Handcrafted superpixel selection and inspection for Visual eXplanations. CoRR abs/2111.08094 (2021) - 2020
- [j15]Rafal Cylwa, Kornel Kielczewski, Marta Machnik, Urszula Oleksiewicz
, Przemyslaw Biecek:
KRAB ZNF explorer - the online tool for the exploration of the transcriptomic profiles of KRAB-ZNF factors in The Cancer Genome Atlas. Bioinform. 36(3): 980-981 (2020) - [c9]Andreas Holzinger
, Anna Saranti
, Christoph Molnar
, Przemyslaw Biecek
, Wojciech Samek
:
Explainable AI Methods - A Brief Overview. xxAI@ICML 2020: 13-38 - [c8]Adam Gabriel Dobrakowski, Agnieszka Mykowiecka, Malgorzata Marciniak, Wojciech Jaworski, Przemyslaw Biecek:
Interpretable Segmentation of Medical Free-Text Records Based on Word Embeddings. ISMIS 2020: 45-55 - [c7]Michal Kuzba
, Przemyslaw Biecek
:
What Would You Ask the Machine Learning Model? Identification of User Needs for Model Explanations Based on Human-Model Conversations. PKDD/ECML Workshops 2020: 447-459 - [e1]Irena Koprinska
, Michael Kamp
, Annalisa Appice
, Corrado Loglisci
, Luiza Antonie
, Albrecht Zimmermann
, Riccardo Guidotti
, Özlem Özgöbek, Rita P. Ribeiro
, Ricard Gavaldà
, João Gama
, Linara Adilova, Yamuna Krishnamurthy
, Pedro M. Ferreira
, Donato Malerba
, Ibéria Medeiros
, Michelangelo Ceci
, Giuseppe Manco
, Elio Masciari
, Zbigniew W. Ras
, Peter Christen
, Eirini Ntoutsi, Erich Schubert
, Arthur Zimek
, Anna Monreale
, Przemyslaw Biecek
, Salvatore Rinzivillo
, Benjamin Kille
, Andreas Lommatzsch, Jon Atle Gulla:
ECML PKDD 2020 Workshops - Workshops of the European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD 2020): SoGood 2020, PDFL 2020, MLCS 2020, NFMCP 2020, DINA 2020, EDML 2020, XKDD 2020 and INRA 2020, Ghent, Belgium, September 14-18, 2020, Proceedings. Communications in Computer and Information Science 1323, Springer 2020, ISBN 978-3-030-65964-6 [contents] - [i26]Alicja Gosiewska, Przemyslaw Biecek:
Lifting Interpretability-Performance Trade-off via Automated Feature Engineering. CoRR abs/2002.04267 (2020) - [i25]Katarzyna Woznica, Przemyslaw Biecek:
Towards better understanding of meta-features contributions. CoRR abs/2002.04276 (2020) - [i24]Michal Kuzba
, Przemyslaw Biecek:
What Would You Ask the Machine Learning Model? Identification of User Needs for Model Explanations Based on Human-Model Conversations. CoRR abs/2002.05674 (2020) - [i23]Filip Gralinski, Tomasz Stanislawek, Anna Wróblewska, Dawid Lipinski, Agnieszka Kaliska, Paulina Rosalska, Bartosz Topolski, Przemyslaw Biecek:
Kleister: A novel task for Information Extraction involving Long Documents with Complex Layout. CoRR abs/2003.02356 (2020) - [i22]Hubert Baniecki
, Przemyslaw Biecek:
The Grammar of Interactive Explanatory Model Analysis. CoRR abs/2005.00497 (2020) - [i21]Alicja Gosiewska, Katarzyna Woznica, Przemyslaw Biecek:
Interpretable Meta-Measure for Model Performance. CoRR abs/2006.02293 (2020) - [i20]Katarzyna Woznica, Przemyslaw Biecek:
Does imputation matter? Benchmark for predictive models. CoRR abs/2007.02837 (2020) - [i19]Wojciech Kretowicz, Przemyslaw Biecek:
MementoML: Performance of selected machine learning algorithm configurations on OpenML100 datasets. CoRR abs/2008.13162 (2020) - [i18]Szymon Maksymiuk
, Alicja Gosiewska, Przemyslaw Biecek:
Landscape of R packages for eXplainable Artificial Intelligence. CoRR abs/2009.13248 (2020) - [i17]Michael Bücker
, Gero Szepannek, Alicja Gosiewska, Przemyslaw Biecek:
Transparency, Auditability and eXplainability of Machine Learning Models in Credit Scoring. CoRR abs/2009.13384 (2020) - [i16]Weronika Hryniewska, Przemyslaw Bombinski, Patryk Szatkowski, Paulina Tomaszewska, Artur Przelaskowski, Przemyslaw Biecek:
Do not repeat these mistakes - a critical appraisal of applications of explainable artificial intelligence for image based COVID-19 detection. CoRR abs/2012.08333 (2020) - [i15]Hubert Baniecki
, Wojciech Kretowicz, Piotr Piatyszek, Jakub Wisniewski, Przemyslaw Biecek:
dalex: Responsible Machine Learning with Interactive Explainability and Fairness in Python. CoRR abs/2012.14406 (2020)
2010 – 2019
- 2019
- [j14]Michal Kuzba
, Ewa Baranowska
, Przemyslaw Biecek
:
pyCeterisParibus: explaining Machine Learning models with Ceteris Paribus Profiles in Python. J. Open Source Softw. 4(37): 1389 (2019) - [j13]Kamil Romaszko, Magda Tatarynowicz, Mateusz Urbanski, Przemyslaw Biecek
:
modelDown: automated website generator with interpretable documentation for predictive machine learning models. J. Open Source Softw. 4(38): 1444 (2019) - [j12]Hubert Baniecki
, Przemyslaw Biecek
:
modelStudio: Interactive Studio with Explanations for ML Predictive Models. J. Open Source Softw. 4(43): 1798 (2019) - [j11]Alicja Gosiewska
, Przemyslaw Biecek:
auditor: an R Package for Model-Agnostic Visual Validation and Diagnostics. R J. 11(2): 85 (2019) - [j10]Mateusz Staniak
, Przemyslaw Biecek:
The Landscape of R Packages for Automated Exploratory Data Analysis. R J. 11(2): 347 (2019) - [c6]Katarzyna Kobylinska
, Tomasz Mikolajczyk, Mariusz Adamek
, Tadeusz Orlowski, Przemyslaw Biecek
:
Explainable Machine Learning for Modeling of Early Postoperative Mortality in Lung Cancer. KR4HC/ProHealth/TEAAM@AIME 2019: 161-174 - [c5]Tomasz Stanislawek, Anna Wróblewska
, Alicja Wójcicka
, Daniel Ziembicki, Przemyslaw Biecek:
Named Entity Recognition - Is There a Glass Ceiling? CoNLL 2019: 624-633 - [c4]Barbara Rychalska, Dominika Basaj, Alicja Gosiewska
, Przemyslaw Biecek:
Models in the Wild: On Corruption Robustness of Neural NLP Systems. ICONIP (3) 2019: 235-247 - [i14]Alicja Gosiewska, Aleksandra Gacek, Piotr Lubon, Przemyslaw Biecek
:
SAFE ML: Surrogate Assisted Feature Extraction for Model Learning. CoRR abs/1902.11035 (2019) - [i13]Alicja Gosiewska, Przemyslaw Biecek
:
iBreakDown: Uncertainty of Model Explanations for Non-additive Predictive Models. CoRR abs/1903.11420 (2019) - [i12]Mateusz Staniak, Przemyslaw Biecek:
The Landscape of R Packages for Automated Exploratory Data Analysis. CoRR abs/1904.02101 (2019) - [i11]Adam Gabriel Dobrakowski, Agnieszka Mykowiecka, Malgorzata Marciniak, Wojciech Jaworski, Przemyslaw Biecek:
Clustering of Medical Free-Text Records Based on Word Embeddings. CoRR abs/1907.04152 (2019) - [i10]Przemyslaw Biecek:
Model Development Process. CoRR abs/1907.04461 (2019) - [i9]Alicja Gosiewska, Mateusz Bakala, Katarzyna Woznica, Maciej Zwolinski, Przemyslaw Biecek:
EPP: interpretable score of model predictive power. CoRR abs/1908.09213 (2019) - [i8]Tomasz Stanislawek, Anna Wróblewska, Alicja Wójcicka, Daniel Ziembicki, Przemyslaw Biecek:
Named Entity Recognition - Is there a glass ceiling? CoRR abs/1910.02403 (2019) - 2018
- [j9]Przemyslaw Biecek:
DALEX: Explainers for Complex Predictive Models in R. J. Mach. Learn. Res. 19: 84:1-84:5 (2018) - [j8]Aleksandra Grudziaz
, Alicja Gosiewska
, Przemyslaw Biecek
:
survxai: an R package for structure-agnostic explanations of survival models. J. Open Source Softw. 3(31): 961 (2018) - [j7]Mateusz Staniak
, Przemyslaw Biecek:
Explanations of Model Predictions with live and breakDown Packages. R J. 10(2): 395 (2018) - [c3]Barbara Rychalska, Dominika Basaj, Anna Wróblewska, Przemyslaw Biecek:
How much should you ask? On the question structure in QA systems. BlackboxNLP@EMNLP 2018: 319-321 - [c2]Barbara Rychalska, Dominika Basaj, Anna Wróblewska, Przemyslaw Biecek:
Does it care what you asked? Understanding Importance of Verbs in Deep Learning QA System. BlackboxNLP@EMNLP 2018: 322-324 - [i7]Mateusz Staniak, Przemyslaw Biecek:
Explanations of model predictions with live and breakDown packages. CoRR abs/1804.01955 (2018) - [i6]Przemyslaw Biecek:
DALEX: explainers for complex predictive models. CoRR abs/1806.08915 (2018) - [i5]Dominika Basaj, Barbara Rychalska, Przemyslaw Biecek, Anna Wróblewska:
How much should you ask? On the question structure in QA systems. CoRR abs/1809.03734 (2018) - [i4]Barbara Rychalska, Dominika Basaj, Przemyslaw Biecek, Anna Wróblewska:
Does it care what you asked? Understanding Importance of Verbs in Deep Learning QA System. CoRR abs/1809.03740 (2018) - [i3]Alicja Gosiewska, Przemyslaw Biecek:
auditor: an R Package for Model-Agnostic Visual Validation and Diagnostic. CoRR abs/1809.07763 (2018) - [i2]Barbara Rychalska, Dominika Basaj, Przemyslaw Biecek:
Are you tough enough? Framework for Robustness Validation of Machine Comprehension Systems. CoRR abs/1812.02205 (2018) - 2017
- [j6]Leo Lahti, Janne Huovari
, Markus Kainu, Przemyslaw Biecek:
Retrieval and Analysis of Eurostat Open Data with the eurostat Package. R J. 9(1): 385 (2017) - [i1]Agnieszka Sitko, Przemyslaw Biecek:
Merge and Select: Visualization of a likelihood based k-sample adaptive fusing and model selection. CoRR abs/1709.04412 (2017) - 2011
- [j5]Ewa Szczurek
, Florian Markowetz
, Irit Gat-Viks, Przemyslaw Biecek
, Jerzy Tiuryn
, Martin Vingron:
Deregulation upon DNA damage revealed by joint analysis of context-specific perturbation data. BMC Bioinform. 12: 249 (2011) - [j4]Norbert Dojer, Przemyslaw Biecek
, Jerzy Tiuryn
:
Bi-Billboard: Symmetrization and Careful Choice of Informant Species Results in Higher Accuracy of Regulatory Element Prediction. J. Comput. Biol. 18(6): 809-819 (2011) - 2010
- [j3]Ewa Szczurek
, Przemyslaw Biecek
, Jerzy Tiuryn
, Martin Vingron:
Introducing Knowledge into Differential Expression Analysis. J. Comput. Biol. 17(8): 953-967 (2010)
2000 – 2009
- 2008
- [c1]Pawel Mackiewicz, Przemyslaw Biecek
, Dorota Mackiewicz
, Joanna Kiraga, Krystian Baczkowski, Maciej Sobczynski
, Stanislaw Cebrat:
Optimisation of Asymmetric Mutational Pressure and Selection Pressure Around the Universal Genetic Code. ICCS (3) 2008: 100-109 - 2007
- [j2]Andreas Baierl
, Andreas Futschik
, Malgorzata Bogdan, Przemyslaw Biecek
:
Locating multiple interacting quantitative trait loci using robust model selection. Comput. Stat. Data Anal. 51(12): 6423-6434 (2007) - [j1]Marta Zawierta, Przemyslaw Biecek
, Wojciech Waga, Stanislaw Cebrat:
The role of intragenomic recombination rate in the evolution of population's genetic pool. Theory Biosci. 125(2): 123-132 (2007)
Coauthor Index
![](https://dblp.org/img/cog.dark.24x24.png)
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