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ORCIDThomas Lukasiewicz
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- affiliation: Vienna University of Technology, Austria
- affiliation: University of Oxford, UK
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2020 – today
- 2025
[j86]Zhenghua Xu, Yunxin Liu, Gang Xu, Thomas Lukasiewicz:
Self-Supervised Medical Image Segmentation Using Deep Reinforced Adaptive Masking. IEEE Trans. Medical Imaging 44(1): 180-193 (2025)- 2024
- [j85]Vid Kocijan
, Myeongjun Erik Jang, Thomas Lukasiewicz:
Pre-training and diagnosing knowledge base completion models. Artif. Intell. 329: 104081 (2024) - [j84]Zhenghua Xu, Jiaqi Tang, Chang Qi, Dan Yao, Caihua Liu, Yuefu Zhan, Thomas Lukasiewicz:
Cross-domain attention-guided generative data augmentation for medical image analysis with limited data. Comput. Biol. Medicine 168: 107744 (2024) - [j83]Zhenghua Xu, Shengxin Wang, Gang Xu, Yunxin Liu, Miao Yu, Hongwei Zhang, Thomas Lukasiewicz, Junhua Gu:
Automatic data augmentation for medical image segmentation using Adaptive Sequence-length based Deep Reinforcement Learning. Comput. Biol. Medicine 169: 107877 (2024) - [j82]Eleonora Giunchiglia, Alex Tatomir, Mihaela Catalina Stoian, Thomas Lukasiewicz:
CCN+: A neuro-symbolic framework for deep learning with requirements. Int. J. Approx. Reason. 171: 109124 (2024) - [j81]Louis Mahon, Thomas Lukasiewicz:
Minimum description length clustering to measure meaningful image complexity. Pattern Recognit. 145: 109889 (2024) - [j80]Lei Sha, Thomas Lukasiewicz:
Text Attribute Control via Closed-Loop Disentanglement. Trans. Assoc. Comput. Linguistics 12: 190-209 (2024) - [j79]Jiaojiao Zhang, Shuo Zhang, Xiaoqian Shen, Thomas Lukasiewicz, Zhenghua Xu:
Multi-ConDoS: Multimodal Contrastive Domain Sharing Generative Adversarial Networks for Self-Supervised Medical Image Segmentation. IEEE Trans. Medical Imaging 43(1): 76-95 (2024) - [j78]Louis Mahon, Lei Sha, Thomas Lukasiewicz:
Correcting Flaws in Common Disentanglement Metrics. Trans. Mach. Learn. Res. 2024 (2024) - [j77]Zhenghua Xu, Zhoutao Yu, Hexiang Zhang, Junyang Chen, Junhua Gu, Thomas Lukasiewicz, Victor C. M. Leung:
PhaCIA-TCNs: Short-Term Load Forecasting Using Temporal Convolutional Networks With Parallel Hybrid Activated Convolution and Input Attention. IEEE Trans. Netw. Sci. Eng. 11(1): 427-438 (2024) - [j76]Zhenghua Xu, Biao Tian, Shijie Liu, Xiangtao Wang, Di Yuan, Junhua Gu, Junyang Chen, Thomas Lukasiewicz, Victor C. M. Leung:
Collaborative Attention Guided Multi-Scale Feature Fusion Network for Medical Image Segmentation. IEEE Trans. Netw. Sci. Eng. 11(2): 1857-1871 (2024) - [c238]Louis Mahon, Thomas Lukasiewicz:
Hard Regularization to Prevent Deep Online Clustering Collapse without Data Augmentation. AAAI 2024: 14281-14288 - [c237]Vid Kocijan, Ernest Davis, Thomas Lukasiewicz, Gary Marcus, Leora Morgenstern:
The Defeat of the Winograd Schema Challenge (Abstract Reprint). AAAI 2024: 22703 - [c236]Maxime Kayser, Bayar Menzat, Cornelius Emde, Bogdan Bercean, Alex Novak, Abdalá Morgado, Bartlomiej W. Papiez, Susanne Gaube, Thomas Lukasiewicz, Oana-Maria Camburu:
Fool Me Once? Contrasting Textual and Visual Explanations in a Clinical Decision-Support Setting. EMNLP 2024: 18891-18919 - [c235]Simon Frieder, Mirek Olsák, Julius Berner, Thomas Lukasiewicz:
The IMO Small Challenge: Not-Too-Hard Olympiad Math Datasets for LLMs. Tiny Papers @ ICLR 2024 - [c234]Simon Frieder, Luca Pinchetti, Thomas Lukasiewicz:
Bad Predictive Coding Activation Functions. Tiny Papers @ ICLR 2024 - [c233]Tommaso Salvatori, Yuhang Song, Yordan Yordanov, Beren Millidge, Lei Sha, Cornelius Emde, Zhenghua Xu, Rafal Bogacz, Thomas Lukasiewicz:
A Stable, Fast, and Fully Automatic Learning Algorithm for Predictive Coding Networks. ICLR 2024 - [c232]Mihaela C. Stoian, Salijona Dyrmishi, Maxime Cordy, Thomas Lukasiewicz, Eleonora Giunchiglia:
How Realistic Is Your Synthetic Data? Constraining Deep Generative Models for Tabular Data. ICLR 2024 - [c231]Tommaso Salvatori, Luca Pinchetti, Amine M'Charrak, Beren Millidge, Thomas Lukasiewicz:
Predictive Coding beyond Correlations. ICML 2024 - [c230]Mihaela C. Stoian, Alex Tatomir, Thomas Lukasiewicz, Eleonora Giunchiglia:
PiShield: A PyTorch Package for Learning with Requirements. IJCAI 2024: 8805-8809 - [i122]Vid Kocijan, Myeongjun Erik Jang, Thomas Lukasiewicz:
Pre-training and Diagnosing Knowledge Base Completion Models. CoRR abs/2401.15439 (2024) - [i121]Mihaela Catalina Stoian, Salijona Dyrmishi, Maxime Cordy, Thomas Lukasiewicz, Eleonora Giunchiglia:
How Realistic Is Your Synthetic Data? Constraining Deep Generative Models for Tabular Data. CoRR abs/2402.04823 (2024) - [i120]Tommaso Salvatori, Beren Millidge, Yuhang Song, Rafal Bogacz, Thomas Lukasiewicz:
Associative Memories in the Feature Space. CoRR abs/2402.10814 (2024) - [i119]Mihaela Catalina Stoian, Eleonora Giunchiglia, Thomas Lukasiewicz:
Exploiting T-norms for Deep Learning in Autonomous Driving. CoRR abs/2402.11362 (2024) - [i118]Mihaela Catalina Stoian, Alex Tatomir, Thomas Lukasiewicz, Eleonora Giunchiglia:
PiShield: A NeSy Framework for Learning with Requirements. CoRR abs/2402.18285 (2024) - [i117]Cornelius Emde, Francesco Pinto, Thomas Lukasiewicz, Philip H. S. Torr, Adel Bibi:
Towards Certification of Uncertainty Calibration under Adversarial Attacks. CoRR abs/2405.13922 (2024) - [i116]Luca Pinchetti, Chang Qi, Oleh Lokshyn, Gaspard Olivers, Cornelius Emde, Mufeng Tang, Amine M'Charrak, Simon Frieder, Bayar Menzat, Rafal Bogacz, Thomas Lukasiewicz, Tommaso Salvatori:
Benchmarking Predictive Coding Networks - Made Simple. CoRR abs/2407.01163 (2024) - [i115]Zehua Cheng, Di Yuan, Thomas Lukasiewicz:
Affinity-Graph-Guided Contractive Learning for Pretext-Free Medical Image Segmentation with Minimal Annotation. CoRR abs/2410.10366 (2024) - [i114]Maxime Kayser, Bayar Menzat, Cornelius Emde, Bogdan Bercean, Alex Novak, Abdala Espinosa, Bartlomiej W. Papiez, Susanne Gaube, Thomas Lukasiewicz, Oana-Maria Camburu:
Fool Me Once? Contrasting Textual and Visual Explanations in a Clinical Decision-Support Setting. CoRR abs/2410.12284 (2024) - [i113]Simon Frieder, Jonas Bayer, Katherine M. Collins, Julius Berner, Jacob Loader, András Juhász, Fabian Ruehle, Sean Welleck, Gabriel Poesia, Ryan-Rhys Griffiths, Adrian Weller, Anirudh Goyal, Thomas Lukasiewicz, Timothy Gowers:
Data for Mathematical Copilots: Better Ways of Presenting Proofs for Machine Learning. CoRR abs/2412.15184 (2024) - 2023
- [j75]Lei Sha, Oana-Maria Camburu, Thomas Lukasiewicz:
Rationalizing predictions by adversarial information calibration. Artif. Intell. 315: 103828 (2023) - [j74]Vid Kocijan, Ernest Davis, Thomas Lukasiewicz, Gary Marcus, Leora Morgenstern:
The defeat of the Winograd Schema Challenge. Artif. Intell. 325: 103971 (2023) - [j73]Di Yuan, Yunxin Liu, Zhenghua Xu, Yuefu Zhan, Junyang Chen, Thomas Lukasiewicz:
Painless and accurate medical image analysis using deep reinforcement learning with task-oriented homogenized automatic pre-processing. Comput. Biol. Medicine 153: 106487 (2023) - [j72]Di Yuan, Zhenghua Xu, Biao Tian, Hening Wang, Yuefu Zhan, Thomas Lukasiewicz:
μ-Net: Medical image segmentation using efficient and effective deep supervision. Comput. Biol. Medicine 160: 106963 (2023) - [j71]Zhenghua Xu, Xudong Zhang, Hexiang Zhang, Yunxin Liu, Yuefu Zhan, Thomas Lukasiewicz:
EFPN: Effective medical image detection using feature pyramid fusion enhancement. Comput. Biol. Medicine 163: 107149 (2023) - [j70]Miao Yu, Miaomiao Guo, Shuai Zhang, Yuefu Zhan, Mingkang Zhao, Thomas Lukasiewicz, Zhenghua Xu:
RIRGAN: An end-to-end lightweight multi-task learning method for brain MRI super-resolution and denoising. Comput. Biol. Medicine 167: 107632 (2023) - [j69]Shuo Zhang, Jiaojiao Zhang, Biao Tian, Thomas Lukasiewicz, Zhenghua Xu:
Multi-modal contrastive mutual learning and pseudo-label re-learning for semi-supervised medical image segmentation. Medical Image Anal. 83: 102656 (2023) - [j68]Eleonora Giunchiglia, Mihaela Catalina Stoian, Salman Khan, Fabio Cuzzolin, Thomas Lukasiewicz:
ROAD-R: the autonomous driving dataset with logical requirements. Mach. Learn. 112(9): 3261-3291 (2023) - [j67]Mufeng Tang, Tommaso Salvatori, Beren Millidge, Yuhang Song, Thomas Lukasiewicz, Rafal Bogacz:
Recurrent predictive coding models for associative memory employing covariance learning. PLoS Comput. Biol. 19(4) (2023) - [j66]Yikuan Li, Mohammad Mamouei, Gholamreza Salimi-Khorshidi, Shishir Rao, Abdelaali Hassaïne, Dexter Canoy, Thomas Lukasiewicz, Kazem Rahimi:
Hi-BEHRT: Hierarchical Transformer-Based Model for Accurate Prediction of Clinical Events Using Multimodal Longitudinal Electronic Health Records. IEEE J. Biomed. Health Informatics 27(2): 1106-1117 (2023) - [j65]Haozhe Lin, Yushun Fan, Jia Zhang, Bing Bai, Zhenghua Xu, Thomas Lukasiewicz:
Toward Knowledge as a Service (KaaS): Predicting Popularity of Knowledge Services Leveraging Graph Neural Networks. IEEE Trans. Serv. Comput. 16(1): 642-655 (2023) - [c229]Pepa Atanasova, Oana-Maria Camburu, Christina Lioma, Thomas Lukasiewicz, Jakob Grue Simonsen, Isabelle Augenstein:
Faithfulness Tests for Natural Language Explanations. ACL (2) 2023: 283-294 - [c228]Myeongjun Jang, Bodhisattwa Prasad Majumder, Julian J. McAuley, Thomas Lukasiewicz, Oana-Maria Camburu:
KNOW How to Make Up Your Mind! Adversarially Detecting and Alleviating Inconsistencies in Natural Language Explanations. ACL (2) 2023: 540-553 - [c227]Zhongbin Xie, Thomas Lukasiewicz:
An Empirical Analysis of Parameter-Efficient Methods for Debiasing Pre-Trained Language Models. ACL (1) 2023: 15730-15745 - [c226]Felix Jackson, Thomas Lukasiewicz:
Deconvolution of cell-free DNA in cancer liquid biopsy using a deep AutoEncoder. BCB 2023: 32:1-32:6 - [c225]Zhongbin Xie, Vid Kocijan, Thomas Lukasiewicz, Oana-Maria Camburu:
Counter-GAP: Counterfactual Bias Evaluation through Gendered Ambiguous Pronouns. EACL 2023: 3743-3755 - [c224]Tommaso Salvatori, Beren Millidge, Yuhang Song, Rafal Bogacz, Thomas Lukasiewicz:
Associative Memories in the Feature Space. ECAI 2023: 2065-2072 - [c223]Myeongjun Jang, Thomas Lukasiewicz:
Improving Language Models' Meaning Understanding and Consistency by Learning Conceptual Roles from Dictionary. EMNLP 2023: 8496-8510 - [c222]Myeongjun Jang, Thomas Lukasiewicz:
Consistency Analysis of ChatGPT. EMNLP 2023: 15970-15985 - [c221]Xiangtao Wang, Ruizhi Wang, Biao Tian, Jiaojiao Zhang, Shuo Zhang, Junyang Chen, Thomas Lukasiewicz, Zhenghua Xu:
MPS-AMS: Masked Patches Selection and Adaptive Masking Strategy Based Self-Supervised Medical Image Segmentation. ICASSP 2023: 1-5 - [c220]Ruizhi Wang, Xiangtao Wang, Zhenghua Xu, Wenting Xu, Junyang Chen, Thomas Lukasiewicz:
MvCo-DoT: Multi-View Contrastive Domain Transfer Network for Medical Report Generation. ICASSP 2023: 1-5 - [c219]Hexiang Zhang, Zhenghua Xu, Dan Yao, Shuo Zhang, Junyang Chen, Thomas Lukasiewicz:
Multi-Head Feature Pyramid Networks for Breast Mass Detection. ICASSP 2023: 1-5 - [c218]Beren Millidge, Yuhang Song, Tommaso Salvatori, Thomas Lukasiewicz, Rafal Bogacz:
Backpropagation at the Infinitesimal Inference Limit of Energy-Based Models: Unifying Predictive Coding, Equilibrium Propagation, and Contrastive Hebbian Learning. ICLR 2023 - [c217]Beren Millidge, Yuhang Song, Tommaso Salvatori, Thomas Lukasiewicz, Rafal Bogacz:
A Theoretical Framework for Inference and Learning in Predictive Coding Networks. ICLR 2023 - [c216]Gang Xu, Shengxin Wang, Thomas Lukasiewicz, Zhenghua Xu:
Adaptive-Masking Policy with Deep Reinforcement Learning for Self-Supervised Medical Image Segmentation. ICME 2023: 2285-2290 - [c215]Jianfeng Wang, Daniela Massiceti, Xiaolin Hu, Vladimir Pavlovic, Thomas Lukasiewicz:
NP-SemiSeg: When Neural Processes meet Semi-Supervised Semantic Segmentation. ICML 2023: 36138-36156 - [c214]Thomas Lukasiewicz, Enrico Malizia, Cristian Molinaro:
Complexity of Inconsistency-Tolerant Query Answering in Datalog+/- under Preferred Repairs. KR 2023: 472-481 - [c213]Mihaela C. Stoian, Eleonora Giunchiglia, Thomas Lukasiewicz:
Exploiting T-norms for Deep Learning in Autonomous Driving. NeSy 2023: 369-380 - [c212]Simon Frieder, Luca Pinchetti, Alexis Chevalier, Ryan-Rhys Griffiths, Tommaso Salvatori, Thomas Lukasiewicz, Philipp Petersen, Julius Berner:
Mathematical Capabilities of ChatGPT. NeurIPS 2023 - [i112]Lei Sha, Oana-Maria Camburu, Thomas Lukasiewicz:
Rationalizing Predictions by Adversarial Information Calibration. CoRR abs/2301.06009 (2023) - [i111]Jianfeng Wang, Xiaolin Hu, Thomas Lukasiewicz:
NP-Match: Towards a New Probabilistic Model for Semi-Supervised Learning. CoRR abs/2301.13569 (2023) - [i110]Simon Frieder, Luca Pinchetti, Ryan-Rhys Griffiths, Tommaso Salvatori, Thomas Lukasiewicz, Philipp Christian Petersen, Alexis Chevalier, Julius Berner:
Mathematical Capabilities of ChatGPT. CoRR abs/2301.13867 (2023) - [i109]Zhongbin Xie, Vid Kocijan, Thomas Lukasiewicz, Oana-Maria Camburu:
Counter-GAP: Counterfactual Bias Evaluation through Gendered Ambiguous Pronouns. CoRR abs/2302.05674 (2023) - [i108]Hexiang Zhang, Zhenghua Xu, Dan Yao, Shuo Zhang, Junyang Chen, Thomas Lukasiewicz:
Multi-Head Feature Pyramid Networks for Breast Mass Detection. CoRR abs/2302.11106 (2023) - [i107]Xiangtao Wang, Ruizhi Wang, Biao Tian, Jiaojiao Zhang, Shuo Zhang, Junyang Chen, Thomas Lukasiewicz, Zhenghua Xu:
MPS-AMS: Masked Patches Selection and Adaptive Masking Strategy Based Self-Supervised Medical Image Segmentation. CoRR abs/2302.13699 (2023) - [i106]Myeongjun Jang, Thomas Lukasiewicz:
Consistency Analysis of ChatGPT. CoRR abs/2303.06273 (2023) - [i105]Louis Mahon, Thomas Lukasiewicz:
Hard Regularization to Prevent Collapse in Online Deep Clustering without Data Augmentation. CoRR abs/2303.16521 (2023) - [i104]Louis Mahon, Lei Shah, Thomas Lukasiewicz:
Correcting Flaws in Common Disentanglement Metrics. CoRR abs/2304.02335 (2023) - [i103]Eleonora Giunchiglia, Fergus Imrie, Mihaela van der Schaar, Thomas Lukasiewicz:
Machine Learning with Requirements: a Manifesto. CoRR abs/2304.03674 (2023) - [i102]Ruizhi Wang, Xiangtao Wang, Zhenghua Xu, Wenting Xu, Junyang Chen, Thomas Lukasiewicz:
MvCo-DoT: Multi-View Contrastive Domain Transfer Network for Medical Report Generation. CoRR abs/2304.07465 (2023) - [i101]Pepa Atanasova, Oana-Maria Camburu, Christina Lioma, Thomas Lukasiewicz, Jakob Grue Simonsen, Isabelle Augenstein:
Faithfulness Tests for Natural Language Explanations. CoRR abs/2305.18029 (2023) - [i100]Katherine M. Collins, Albert Q. Jiang, Simon Frieder, Lionel Wong, Miri Zilka, Umang Bhatt, Thomas Lukasiewicz, Yuhuai Wu, Joshua B. Tenenbaum, William Hart, Timothy Gowers, Wenda Li, Adrian Weller, Mateja Jamnik:
Evaluating Language Models for Mathematics through Interactions. CoRR abs/2306.01694 (2023) - [i99]Myeongjun Jang, Bodhisattwa Prasad Majumder, Julian J. McAuley, Thomas Lukasiewicz, Oana-Maria Camburu:
KNOW How to Make Up Your Mind! Adversarially Detecting and Alleviating Inconsistencies in Natural Language Explanations. CoRR abs/2306.02980 (2023) - [i98]Zhongbin Xie, Thomas Lukasiewicz:
An Empirical Analysis of Parameter-Efficient Methods for Debiasing Pre-Trained Language Models. CoRR abs/2306.04067 (2023) - [i97]Louis Mahon, Thomas Lukasiewicz:
Minimum Description Length Clustering to Measure Meaningful Image Complexity. CoRR abs/2306.14937 (2023) - [i96]Tommaso Salvatori, Luca Pinchetti, Amine M'Charrak, Beren Millidge, Thomas Lukasiewicz:
Causal Inference via Predictive Coding. CoRR abs/2306.15479 (2023) - [i95]Jianfeng Wang, Daniela Massiceti, Xiaolin Hu, Vladimir Pavlovic, Thomas Lukasiewicz:
NP-SemiSeg: When Neural Processes meet Semi-Supervised Semantic Segmentation. CoRR abs/2308.02866 (2023) - [i94]Tommaso Salvatori, Ankur Arjun Mali, Christopher L. Buckley, Thomas Lukasiewicz, Rajesh P. N. Rao, Karl J. Friston, Alexander Ororbia:
Brain-Inspired Computational Intelligence via Predictive Coding. CoRR abs/2308.07870 (2023) - [i93]Xiangtao Wang, Ruizhi Wang, Jie Zhou, Thomas Lukasiewicz, Zhenghua Xu:
AMLP: Adaptive Masking Lesion Patches for Self-supervised Medical Image Segmentation. CoRR abs/2309.04312 (2023) - [i92]Ruizhi Wang, Xiangtao Wang, Jie Zhou, Thomas Lukasiewicz, Zhenghua Xu:
C^2M-DoT: Cross-modal consistent multi-view medical report generation with domain transfer network. CoRR abs/2310.05355 (2023) - [i91]Myeongjun Erik Jang, Thomas Lukasiewicz:
Improving Language Models Meaning Understanding and Consistency by Learning Conceptual Roles from Dictionary. CoRR abs/2310.15541 (2023) - [i90]Lei Sha, Thomas Lukasiewicz:
Text Attribute Control via Closed-Loop Disentanglement. CoRR abs/2312.00277 (2023) - [i89]Simon Frieder, Julius Berner, Philipp Petersen, Thomas Lukasiewicz:
Large Language Models for Mathematicians. CoRR abs/2312.04556 (2023) - 2022
- [j64]Thomas Lukasiewicz, Enrico Malizia:
Complexity results for preference aggregation over (m)CP-nets: Max and rank voting. Artif. Intell. 303: 103636 (2022) - [j63]Thomas Lukasiewicz, Enrico Malizia, Maria Vanina Martinez, Cristian Molinaro, Andreas Pieris, Gerardo I. Simari:
Inconsistency-tolerant query answering for existential rules. Artif. Intell. 307: 103685 (2022) - [j62]Zhenghua Xu, Shijie Liu, Di Yuan, Lei Wang, Junyang Chen, Thomas Lukasiewicz, Zhigang Fu, Rui Zhang:
ω-net: Dual supervised medical image segmentation with multi-dimensional self-attention and diversely-connected multi-scale convolution. Neurocomputing 500: 177-190 (2022) - [j61]Myeongjun Jang, Thomas Lukasiewicz:
NoiER: An Approach for Training More Reliable Fine-Tuned Downstream Task Models. IEEE ACM Trans. Audio Speech Lang. Process. 30: 2514-2525 (2022) - [j60]Shishir Rao, Yikuan Li, Rema Ramakrishnan, Abdelaali Hassaïne, Dexter Canoy, John G. F. Cleland, Thomas Lukasiewicz, Gholamreza Salimi Khorshidi, Kazem Rahimi:
An Explainable Transformer-Based Deep Learning Model for the Prediction of Incident Heart Failure. IEEE J. Biomed. Health Informatics 26(7): 3362-3372 (2022) - [c211]Tommaso Salvatori, Yuhang Song, Zhenghua Xu, Thomas Lukasiewicz, Rafal Bogacz:
Reverse Differentiation via Predictive Coding. AAAI 2022: 8150-8158 - [c210]Louis Mahon, Thomas Lukasiewicz:
Efficient Deep Clustering of Human Activities and How to Improve Evaluation. ACML 2022: 722-737 - [c209]Thomas Lukasiewicz, Enrico Malizia:
Pareto and Majority Voting in mCP-nets. DP@AI*IA 2022: 23-31 - [c208]Ismail Ilkan Ceylan, Thomas Lukasiewicz, Enrico Malizia, Cristian Molinaro, Andrius Vaicenavicius:
Explanations for Negative Query Answers under Existential Rules. DP@AI*IA 2022: 65-74 - [c207]Bowen Li, Philip H. S. Torr, Thomas Lukasiewicz:
Image-to-Image Translation with Text Guidance. BMVC 2022: 581 - [c206]Bowen Li, Philip H. S. Torr, Thomas Lukasiewicz:
Memory-Driven Text-to-Image Generation. BMVC 2022: 726 - [c205]Myeongjun Jang, Deuk Sin Kwon, Thomas Lukasiewicz:
BECEL: Benchmark for Consistency Evaluation of Language Models. COLING 2022: 3680-3696 - [c204]Jianfeng Wang, Thomas Lukasiewicz:
Rethinking Bayesian Deep Learning Methods for Semi-Supervised Volumetric Medical Image Segmentation. CVPR 2022: 182-190 - [c203]Zehua Cheng, Lianlong Wu, Thomas Lukasiewicz, Emanuel Sallinger, Georg Gottlob:
Democratizing Financial Knowledge Graph Construction by Mining Massive Brokerage Research Reports. EDBT/ICDT Workshops 2022 - [c202]Yordan Yordanov, Vid Kocijan, Thomas Lukasiewicz, Oana-Maria Camburu:
Few-Shot Out-of-Domain Transfer Learning of Natural Language Explanations in a Label-Abundant Setup. EMNLP (Findings) 2022: 3486-3501 - [c201]Bowen Li, Thomas Lukasiewicz:
Learning to Model Multimodal Semantic Alignment for Story Visualization. EMNLP (Findings) 2022: 4712-4718 - [c200]Frank Mtumbuka, Thomas Lukasiewicz:
Syntactically Rich Discriminative Training: An Effective Method for Open Information Extraction. EMNLP 2022: 5972-5987 - [c199]Simon Frieder, Thomas Lukasiewicz:
(Non-)Convergence Results for Predictive Coding Networks. ICML 2022: 6793-6810 - [c198]Bodhisattwa Prasad Majumder, Oana Camburu, Thomas Lukasiewicz, Julian J. McAuley:
Knowledge-Grounded Self-Rationalization via Extractive and Natural Language Explanations. ICML 2022: 14786-14801 - [c197]Beren Millidge, Tommaso Salvatori, Yuhang Song, Thomas Lukasiewicz, Rafal Bogacz:
Universal Hopfield Networks: A General Framework for Single-Shot Associative Memory Models. ICML 2022: 15561-15583 - [c196]Jianfeng Wang, Thomas Lukasiewicz, Daniela Massiceti, Xiaolin Hu, Vladimir Pavlovic, Alexandros Neophytou:
NP-Match: When Neural Processes meet Semi-Supervised Learning. ICML 2022: 22919-22934 - [c195]Thomas Lukasiewicz, Enrico Malizia, Cristian Molinaro:
Explanations for Negative Query Answers under Inconsistency-Tolerant Semantics. IJCAI 2022: 2705-2711 - [c194]Eleonora Giunchiglia, Mihaela Catalina Stoian, Thomas Lukasiewicz:
Deep Learning with Logical Constraints. IJCAI 2022: 5478-5485 - [c193]Beren Millidge, Tommaso Salvatori, Yuhang Song, Rafal Bogacz, Thomas Lukasiewicz:
Predictive Coding: Towards a Future of Deep Learning beyond Backpropagation? IJCAI 2022: 5538-5545 - [c192]Maxime Kayser, Cornelius Emde, Oana-Maria Camburu, Guy Parsons, Bartlomiej W. Papiez, Thomas Lukasiewicz:
Explaining Chest X-Ray Pathologies in Natural Language. MICCAI (5) 2022: 701-713 - [c191]Bowen Li, Philip H. S. Torr, Thomas Lukasiewicz:
Clustering Generative Adversarial Networks for Story Visualization. ACM Multimedia 2022: 769-778 - [c190]Myeongjun Jang, Frank Mtumbuka, Thomas Lukasiewicz:
Beyond Distributional Hypothesis: Let Language Models Learn Meaning-Text Correspondence. NAACL-HLT (Findings) 2022: 2030-2042 - [c189]Luca Pinchetti, Tommaso Salvatori, Yordan Yordanov, Beren Millidge, Yuhang Song, Thomas Lukasiewicz:
Predictive Coding beyond Gaussian Distributions. NeurIPS 2022 - [c188]Tommaso Salvatori, Luca Pinchetti, Beren Millidge, Yuhang Song, Tianyi Bao, Rafal Bogacz, Thomas Lukasiewicz:
Learning on Arbitrary Graph Topologies via Predictive Coding. NeurIPS 2022 - [c187]Ismail Ilkan Ceylan,