Thomas Lukasiewicz - researchr alias

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Viewing Publication 1 - 100 from 335

2025

2024

Affinity-Graph-Guided Contractive Learning for Pretext-Free Medical Image Segmentation with Minimal AnnotationZehua Cheng, Di Yuan, Thomas Lukasiewicz. bibm 2024: 3127-3133 [doi]

Bad Predictive Coding Activation FunctionsSimon Frieder, Luca Pinchetti, Thomas Lukasiewicz. iclr 2024: [doi]

The IMO Small Challenge: Not-Too-Hard Olympiad Math Datasets for LLMsSimon Frieder, Mirek Olsák, Julius Berner, Thomas Lukasiewicz. iclr 2024: [doi]

CCN+: A neuro-symbolic framework for deep learning with requirementsEleonora Giunchiglia, Alex Tatomir, Mihaela Catalina Stoian, Thomas Lukasiewicz. ijar, 171:109124, 2024. [doi]

Fool Me Once? Contrasting Textual and Visual Explanations in a Clinical Decision-Support SettingMaxime Kayser, Bayar Menzat, Cornelius Emde, Bogdan Bercean, Alex Novak, Abdalá Morgado, Bartlomiej W. Papiez, Susanne Gaube, Thomas Lukasiewicz, Oana-Maria Camburu. emnlp 2024: 18891-18919 [doi]

The Defeat of the Winograd Schema Challenge (Abstract Reprint)Vid Kocijan, Ernest Davis, Thomas Lukasiewicz, Gary Marcus 0001, Leora Morgenstern. AAAI 2024: 22703 [doi]

Pre-training and diagnosing knowledge base completion modelsVid Kocijan, Myeongjun Erik Jang, Thomas Lukasiewicz. ai, 329:104081, 2024. [doi]

On the Complexity of Querying Inconsistent Weighted Knowledge Bases (Short paper)Thomas Lukasiewicz, Enrico Malizia, Cristian Molinaro. aiia 2025: [doi]

Hard Regularization to Prevent Deep Online Clustering Collapse without Data AugmentationLouis Mahon, Thomas Lukasiewicz. AAAI 2024: 14281-14288 [doi]

Minimum description length clustering to measure meaningful image complexityLouis Mahon, Thomas Lukasiewicz. PR, 145:109889, January 2024. [doi]

Correcting Flaws in Common Disentanglement MetricsLouis Mahon, Lei Sha, Thomas Lukasiewicz. tmlr, 2024, 2024. [doi]

Predictive Coding beyond CorrelationsTommaso Salvatori, Luca Pinchetti, Amine M'Charrak, Beren Millidge, Thomas Lukasiewicz. icml 2024: [doi]

A Stable, Fast, and Fully Automatic Learning Algorithm for Predictive Coding NetworksTommaso Salvatori, Yuhang Song 0001, Yordan Yordanov, Beren Millidge, Lei Sha, Cornelius Emde, Zhenghua Xu, Rafal Bogacz, Thomas Lukasiewicz. iclr 2024: [doi]

Text Attribute Control via Closed-Loop DisentanglementLei Sha, Thomas Lukasiewicz. tacl, 12:190-209, 2024. [doi]

PiShield: A PyTorch Package for Learning with RequirementsMihaela C. Stoian, Alex Tatomir, Thomas Lukasiewicz, Eleonora Giunchiglia. IJCAI 2024: 8805-8809 [doi]

How Realistic Is Your Synthetic Data? Constraining Deep Generative Models for Tabular DataMihaela C. Stoian, Salijona Dyrmishi, Maxime Cordy, Thomas Lukasiewicz, Eleonora Giunchiglia. iclr 2024: [doi]

Cross-domain attention-guided generative data augmentation for medical image analysis with limited dataZhenghua Xu, Jiaqi Tang, Chang Qi, Dan Yao, Caihua Liu, Yuefu Zhan, Thomas Lukasiewicz. cbm, 168:107744, January 2024. [doi]

Automatic data augmentation for medical image segmentation using Adaptive Sequence-length based Deep Reinforcement LearningZhenghua Xu, Shengxin Wang, Gang Xu, Yunxin Liu, Miao Yu, Hongwei Zhang, Thomas Lukasiewicz, Junhua Gu. cbm, 169:107877, February 2024. [doi]

PhaCIA-TCNs: Short-Term Load Forecasting Using Temporal Convolutional Networks With Parallel Hybrid Activated Convolution and Input AttentionZhenghua Xu, Zhoutao Yu, Hexiang Zhang, Junyang Chen, Junhua Gu, Thomas Lukasiewicz, Victor C. M. Leung. tnse, 11(1):427-438, January - February 2024. [doi]

Collaborative Attention Guided Multi-Scale Feature Fusion Network for Medical Image SegmentationZhenghua Xu, Biao Tian, Shijie Liu, Xiangtao Wang, Di Yuan, Junhua Gu, Junyang Chen, Thomas Lukasiewicz, Victor C. M. Leung. tnse, 11(2):1857-1871, March - April 2024. [doi]

Multi-ConDoS: Multimodal Contrastive Domain Sharing Generative Adversarial Networks for Self-Supervised Medical Image SegmentationJiaojiao Zhang, Shuo Zhang, Xiaoqian Shen, Thomas Lukasiewicz, Zhenghua Xu. tmi, 43(1):76-95, January 2024. [doi]

2023

Faithfulness Tests for Natural Language ExplanationsPepa Atanasova, Oana-Maria Camburu, Christina Lioma, Thomas Lukasiewicz, Jakob Grue Simonsen, Isabelle Augenstein. acl 2023: 283-294 [doi]

Mathematical Capabilities of ChatGPTSimon Frieder, Luca Pinchetti, Alexis Chevalier, Ryan-Rhys Griffiths, Tommaso Salvatori, Thomas Lukasiewicz, Philipp Petersen, Julius Berner. nips 2023: [doi]

ROAD-R: the autonomous driving dataset with logical requirementsEleonora Giunchiglia, Mihaela Catalina Stoian, Salman Khan 0004, Fabio Cuzzolin, Thomas Lukasiewicz. ml, 112(9):3261-3291, September 2023. [doi]

Deconvolution of cell-free DNA in cancer liquid biopsy using a deep AutoEncoderFelix Jackson, Thomas Lukasiewicz. bcb 2023: [doi]

Improving Language Models' Meaning Understanding and Consistency by Learning Conceptual Roles from DictionaryMyeongjun Jang, Thomas Lukasiewicz. emnlp 2023: 8496-8510 [doi]

Consistency Analysis of ChatGPTMyeongjun Jang, Thomas Lukasiewicz. emnlp 2023: 15970-15985 [doi]

KNOW How to Make Up Your Mind! Adversarially Detecting and Alleviating Inconsistencies in Natural Language ExplanationsMyeongjun Jang, Bodhisattwa Prasad Majumder, Julian J. McAuley, Thomas Lukasiewicz, Oana-Maria Camburu. acl 2023: 540-553 [doi]

The defeat of the Winograd Schema ChallengeVid Kocijan, Ernest Davis, Thomas Lukasiewicz, Gary Marcus 0001, Leora Morgenstern. ai, 325:103971, December 2023. [doi]

Hi-BEHRT: Hierarchical Transformer-Based Model for Accurate Prediction of Clinical Events Using Multimodal Longitudinal Electronic Health RecordsYikuan Li, Mohammad Mamouei, Gholamreza Salimi Khorshidi, Shishir Rao, Abdelaali Hassaïne, Dexter Canoy, Thomas Lukasiewicz, Kazem Rahimi. titb, 27(2):1106-1117, February 2023. [doi]

Toward Knowledge as a Service (KaaS): Predicting Popularity of Knowledge Services Leveraging Graph Neural NetworksHaozhe Lin, Yushun Fan, Jia Zhang 0001, Bing Bai, Zhenghua Xu, Thomas Lukasiewicz. tsc, 16(1):642-655, January - February 2023. [doi]

Complexity of Inconsistency-Tolerant Query Answering in Datalog+/- under Preferred RepairsThomas Lukasiewicz, Enrico Malizia, Cristian Molinaro. kr 2023: 472-481 [doi]

A Theoretical Framework for Inference and Learning in Predictive Coding NetworksBeren Millidge, Yuhang Song 0001, Tommaso Salvatori, Thomas Lukasiewicz, Rafal Bogacz. iclr 2023: [doi]

Backpropagation at the Infinitesimal Inference Limit of Energy-Based Models: Unifying Predictive Coding, Equilibrium Propagation, and Contrastive Hebbian LearningBeren Millidge, Yuhang Song 0001, Tommaso Salvatori, Thomas Lukasiewicz, Rafal Bogacz. iclr 2023: [doi]

Associative Memories in the Feature SpaceTommaso Salvatori, Beren Millidge, Yuhang Song 0001, Rafal Bogacz, Thomas Lukasiewicz. ecai 2023: 2065-2072 [doi]

Rationalizing predictions by adversarial information calibrationLei Sha, Oana-Maria Camburu, Thomas Lukasiewicz. ai, 315:103828, 2023. [doi]

Exploiting T-norms for Deep Learning in Autonomous DrivingMihaela C. Stoian, Eleonora Giunchiglia, Thomas Lukasiewicz. nesy 2023: 369-380 [doi]

Recurrent predictive coding models for associative memory employing covariance learningMufeng Tang, Tommaso Salvatori, Beren Millidge, Yuhang Song 0001, Thomas Lukasiewicz, Rafal Bogacz. ploscb, 19(4), 2023. [doi]

MvCo-DoT: Multi-View Contrastive Domain Transfer Network for Medical Report GenerationRuizhi Wang, Xiangtao Wang, Zhenghua Xu, Wenting Xu, Junyang Chen, Thomas Lukasiewicz. icassp 2023: 1-5 [doi]

NP-SemiSeg: When Neural Processes meet Semi-Supervised Semantic SegmentationJianfeng Wang, Daniela Massiceti, Xiaolin Hu 0001, Vladimir Pavlovic 0001, Thomas Lukasiewicz. icml 2023: 36138-36156 [doi]

MPS-AMS: Masked Patches Selection and Adaptive Masking Strategy Based Self-Supervised Medical Image SegmentationXiangtao Wang, Ruizhi Wang, Biao Tian, Jiaojiao Zhang, Shuo Zhang, Junyang Chen, Thomas Lukasiewicz, Zhenghua Xu. icassp 2023: 1-5 [doi]

An Empirical Analysis of Parameter-Efficient Methods for Debiasing Pre-Trained Language ModelsZhongbin Xie, Thomas Lukasiewicz. acl 2023: 15730-15745 [doi]

Counter-GAP: Counterfactual Bias Evaluation through Gendered Ambiguous PronounsZhongbin Xie, Vid Kocijan, Thomas Lukasiewicz, Oana-Maria Camburu. eacl 2023: 3743-3755 [doi]

Adaptive-Masking Policy with Deep Reinforcement Learning for Self-Supervised Medical Image SegmentationGang Xu, Shengxin Wang, Thomas Lukasiewicz, Zhenghua Xu. icmcs 2023: 2285-2290 [doi]

EFPN: Effective medical image detection using feature pyramid fusion enhancementZhenghua Xu, Xudong Zhang, Hexiang Zhang, Yunxin Liu, Yuefu Zhan, Thomas Lukasiewicz. cbm, 163:107149, September 2023. [doi]

RIRGAN: An end-to-end lightweight multi-task learning method for brain MRI super-resolution and denoisingMiao Yu, Miaomiao Guo, Shuai Zhang, Yuefu Zhan, Mingkang Zhao, Thomas Lukasiewicz, Zhenghua Xu. cbm, 167:107632, December 2023. [doi]

μ-Net: Medical image segmentation using efficient and effective deep supervisionDi Yuan, Zhenghua Xu, Biao Tian, Hening Wang, Yuefu Zhan, Thomas Lukasiewicz. cbm, 160:106963, June 2023. [doi]

Painless and accurate medical image analysis using deep reinforcement learning with task-oriented homogenized automatic pre-processingDi Yuan, Yunxin Liu, Zhenghua Xu, Yuefu Zhan, Junyang Chen, Thomas Lukasiewicz. cbm, 153:106487, February 2023. [doi]

Multi-Head Feature Pyramid Networks for Breast Mass DetectionHexiang Zhang, Zhenghua Xu, Dan Yao, Shuo Zhang, Junyang Chen, Thomas Lukasiewicz. icassp 2023: 1-5 [doi]

Multi-modal contrastive mutual learning and pseudo-label re-learning for semi-supervised medical image segmentationShuo Zhang, Jiaojiao Zhang, Biao Tian, Thomas Lukasiewicz, Zhenghua Xu. mia, 83:102656, 2023. [doi]

2022

Memory-Driven Text-to-Image GenerationBowen Li 0001, Philip H. S. Torr, Thomas Lukasiewicz. bmvc 2022: 726 [doi]

Clustering Generative Adversarial Networks for Story VisualizationBowen Li 0001, Philip H. S. Torr, Thomas Lukasiewicz. mm 2022: 769-778 [doi]

Image-to-Image Translation with Text GuidanceBowen Li 0001, Philip H. S. Torr, Thomas Lukasiewicz. bmvc 2022: 581 [doi]

Learning to Model Multimodal Semantic Alignment for Story VisualizationBowen Li 0001, Thomas Lukasiewicz. emnlp 2022: 4712-4718 [doi]

Explanations for Negative Query Answers under Existential RulesIsmail Ilkan Ceylan, Thomas Lukasiewicz, Enrico Malizia, Cristian Molinaro, Andrius Vaicenavicius. aiia 2023: 65-74 [doi]

Query Answer Explanations under Existential RulesIsmail Ilkan Ceylan, Thomas Lukasiewicz, Enrico Malizia, Andrius Vaicenavicius. sebd 2022: 481-488 [doi]

Democratizing Financial Knowledge Graph Construction by Mining Massive Brokerage Research ReportsZehua Cheng, Lianlong Wu, Thomas Lukasiewicz, Emanuel Sallinger, Georg Gottlob. edbt 2022: [doi]

(Non-)Convergence Results for Predictive Coding NetworksSimon Frieder, Thomas Lukasiewicz. icml 2022: 6793-6810 [doi]

Deep Learning with Logical ConstraintsEleonora Giunchiglia, Mihaela Catalina Stoian, Thomas Lukasiewicz. IJCAI 2022: 5478-5485 [doi]

Beyond Distributional Hypothesis: Let Language Models Learn Meaning-Text CorrespondenceM. j Jang, Frank Mtumbuka, Thomas Lukasiewicz. naacl 2022: 2030-2042 [doi]

BECEL: Benchmark for Consistency Evaluation of Language ModelsMyeongjun Jang, Deuk Sin Kwon, Thomas Lukasiewicz. COLING 2022: 3680-3696 [doi]

NoiER: An Approach for Training More Reliable Fine-Tuned Downstream Task ModelsMyeongjun Jang, Thomas Lukasiewicz. taslp, 30:2514-2525, 2022. [doi]

Explaining Chest X-Ray Pathologies in Natural LanguageMaxime Kayser, Cornelius Emde, Oana-Maria Camburu, Guy Parsons, Bartlomiej W. Papiez, Thomas Lukasiewicz. miccai 2022: 701-713 [doi]

Pareto and Majority Voting in mCP-netsThomas Lukasiewicz, Enrico Malizia. aiia 2023: 23-31 [doi]

Explanations for Negative Query Answers under Inconsistency-Tolerant SemanticsThomas Lukasiewicz, Enrico Malizia, Cristian Molinaro. IJCAI 2022: 2705-2711 [doi]

Complexity of Inconsistency-Tolerant Query Answering in Datalog+/- under Cardinality-Based RepairsThomas Lukasiewicz, Enrico Malizia, Andrius Vaicenavicius. sebd 2022: 530-537 [doi]

Explanations for Inconsistency-Tolerant Query Answering under Existential RulesThomas Lukasiewicz, Enrico Malizia, Cristian Molinaro. sebd 2022: 489-496 [doi]

m)CP-nets: Max and rank votingThomas Lukasiewicz, Enrico Malizia. ai, 303:103636, 2022. [doi]

Inconsistency-tolerant query answering for existential rulesThomas Lukasiewicz, Enrico Malizia, Maria Vanina Martinez, Cristian Molinaro, Andreas Pieris, Gerardo I. Simari. ai, 307:103685, 2022. [doi]

Efficient Deep Clustering of Human Activities and How to Improve EvaluationLouis Mahon, Thomas Lukasiewicz. acml 2022: 722-737 [doi]

Knowledge-Grounded Self-Rationalization via Extractive and Natural Language ExplanationsBodhisattwa Prasad Majumder, Oana Camburu, Thomas Lukasiewicz, Julian J. McAuley. icml 2022: 14786-14801 [doi]

Universal Hopfield Networks: A General Framework for Single-Shot Associative Memory ModelsBeren Millidge, Tommaso Salvatori, Yuhang Song 0001, Thomas Lukasiewicz, Rafal Bogacz. icml 2022: 15561-15583 [doi]

Predictive Coding: Towards a Future of Deep Learning beyond Backpropagation?Beren Millidge, Tommaso Salvatori, Yuhang Song 0001, Rafal Bogacz, Thomas Lukasiewicz. IJCAI 2022: 5538-5545 [doi]

Syntactically Rich Discriminative Training: An Effective Method for Open Information ExtractionFrank Mtumbuka, Thomas Lukasiewicz. emnlp 2022: 5972-5987 [doi]

Predictive Coding beyond Gaussian DistributionsLuca Pinchetti, Tommaso Salvatori, Yordan Yordanov, Beren Millidge, Yuhang Song 0001, Thomas Lukasiewicz. nips 2022: [doi]

An Explainable Transformer-Based Deep Learning Model for the Prediction of Incident Heart FailureShishir Rao, Yikuan Li, Rema Ramakrishnan, Abdelaali Hassaïne, Dexter Canoy, John Cleland, Thomas Lukasiewicz, Gholamreza Salimi Khorshidi, Kazem Rahimi. titb, 26(7):3362-3372, 2022. [doi]

Learning on Arbitrary Graph Topologies via Predictive CodingTommaso Salvatori, Luca Pinchetti, Beren Millidge, Yuhang Song 0001, Tianyi Bao, Rafal Bogacz, Thomas Lukasiewicz. nips 2022: [doi]

Reverse Differentiation via Predictive CodingTommaso Salvatori, Yuhang Song 0001, Zhenghua Xu, Thomas Lukasiewicz, Rafal Bogacz. AAAI 2022: 8150-8158 [doi]

Rethinking Bayesian Deep Learning Methods for Semi-Supervised Volumetric Medical Image SegmentationJianfeng Wang, Thomas Lukasiewicz. cvpr 2022: 182-190 [doi]

NP-Match: When Neural Processes meet Semi-Supervised LearningJianfeng Wang, Thomas Lukasiewicz, Daniela Massiceti, Xiaolin Hu, Vladimir Pavlovic, Alexandros Neophytou. icml 2022: 22919-22934 [doi]

ω-net: Dual supervised medical image segmentation with multi-dimensional self-attention and diversely-connected multi-scale convolutionZhenghua Xu, Shijie Liu, Di Yuan, Lei Wang, Junyang Chen, Thomas Lukasiewicz, Zhigang Fu, Rui Zhang. ijon, 500:177-190, 2022. [doi]

Few-Shot Out-of-Domain Transfer Learning of Natural Language Explanations in a Label-Abundant SetupYordan Yordanov, Vid Kocijan, Thomas Lukasiewicz, Oana-Maria Camburu. emnlp 2022: 3486-3501 [doi]

2021

The Surprising Power of Graph Neural Networks with Random Node InitializationRalph Abboud, Ismail Ilkan Ceylan, Martin Grohe, Thomas Lukasiewicz. IJCAI 2021: 2112-2118 [doi]

An ontology-based deep learning approach for triple classification with out-of-knowledge-base entitiesElvira Amador-Domínguez, Emilio Serrano, Daniel Manrique, Patrick Hohenecker, Thomas Lukasiewicz. isci, 564:85-102, 2021. [doi]

Preferred Explanations for Ontology-Mediated Queries under Existential RulesIsmail Ilkan Ceylan, Thomas Lukasiewicz, Enrico Malizia, Cristian Molinaro, Andrius Vaicenavicius. AAAI 2021: 6262-6270 [doi]

Multi-Label Classification Neural Networks with Hard Logical ConstraintsEleonora Giunchiglia, Thomas Lukasiewicz. jair, 72:759-818, 2021. [doi]

Stable Model Semantics for Guarded Existential Rules and Description Logics: Decidability and ComplexityGeorg Gottlob, André Hernich, Clemens Kupke, Thomas Lukasiewicz. JACM, 68(5), 2021. [doi]

e-ViL: A Dataset and Benchmark for Natural Language Explanations in Vision-Language TasksMaxime Kayser, Oana-Maria Camburu, Leonard Salewski, Cornelius Emde, Virginie Do, Zeynep Akata, Thomas Lukasiewicz. iccv 2021: 1224-1234 [doi]

Knowledge Base Completion Meets Transfer LearningVid Kocijan, Thomas Lukasiewicz. emnlp 2021: 6521-6533 [doi]

The Gap on Gap: Tackling the Problem of Differing Data Distributions in Bias-Measuring DatasetsVid Kocijan, Oana-Maria Camburu, Thomas Lukasiewicz. AAAI 2021: 13180-13188 [doi]

Selective Pseudo-Label ClusteringLouis Mahon, Thomas Lukasiewicz. ki 2021: 158-178 [doi]

Lightweight Visual Question Answering using Scene GraphsSai Vidyaranya Nuthalapati, Ramraj Chandradevan, Eleonora Giunchiglia, Bowen Li, Maxime Kayser, Thomas Lukasiewicz, Carl Yang. CIKM 2021: 3353-3357 [doi]

Multi-type Disentanglement without Adversarial TrainingLei Sha, Thomas Lukasiewicz. AAAI 2021: 9515-9523 [doi]

Controlling Text Edition by Changing Answers of Specific QuestionsLei Sha, Patrick Hohenecker, Thomas Lukasiewicz. acl 2021: 1288-1299 [doi]

Learning from the Best: Rationalizing Predictions by Adversarial Information CalibrationLei Sha, Oana-Maria Camburu, Thomas Lukasiewicz. AAAI 2021: 13771-13779 [doi]

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