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ORCIDThomas Lukasiewicz
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- affiliation: University of Oxford, UK
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2020 – today
- 2023
[j69]Lei Sha
, Oana-Maria Camburu, Thomas Lukasiewicz:
Rationalizing predictions by adversarial information calibration. Artif. Intell. 315: 103828 (2023)- [j68]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) - [j67]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) - [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) - [c209]Zhongbin Xie, Vid Kocijan, Thomas Lukasiewicz, Oana-Maria Camburu:
Counter-GAP: Counterfactual Bias Evaluation through Gendered Ambiguous Pronouns. EACL 2023: 3743-3755 - [i99]Lei Sha, Oana-Maria Camburu, Thomas Lukasiewicz:
Rationalizing Predictions by Adversarial Information Calibration. CoRR abs/2301.06009 (2023) - [i98]Jianfeng Wang, Xiaolin Hu, Thomas Lukasiewicz:
NP-Match: Towards a New Probabilistic Model for Semi-Supervised Learning. CoRR abs/2301.13569 (2023) - [i97]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) - [i96]Zhongbin Xie, Vid Kocijan, Thomas Lukasiewicz, Oana-Maria Camburu:
Counter-GAP: Counterfactual Bias Evaluation through Gendered Ambiguous Pronouns. CoRR abs/2302.05674 (2023) - [i95]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) - [i94]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) - [i93]Myeongjun Jang, Thomas Lukasiewicz:
Consistency Analysis of ChatGPT. CoRR abs/2303.06273 (2023) - [i92]Louis Mahon, Thomas Lukasiewicz:
Hard Regularization to Prevent Collapse in Online Deep Clustering without Data Augmentation. CoRR abs/2303.16521 (2023) - [i91]Louis Mahon, Lei Shah, Thomas Lukasiewicz:
Correcting Flaws in Common Disentanglement Metrics. CoRR abs/2304.02335 (2023) - [i90]Eleonora Giunchiglia, Fergus Imrie, Mihaela van der Schaar, Thomas Lukasiewicz:
Machine Learning with Requirements: a Manifesto. CoRR abs/2304.03674 (2023) - [i89]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) - 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) - [c208]Tommaso Salvatori, Yuhang Song, Zhenghua Xu, Thomas Lukasiewicz, Rafal Bogacz:
Reverse Differentiation via Predictive Coding. AAAI 2022: 8150-8158 - [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, Thomas Lukasiewicz, Enrico Malizia, Andrius Vaicenavicius:
Query Answer Explanations under Existential Rules. SEBD 2022: 481-488 - [c186]Thomas Lukasiewicz, Enrico Malizia, Cristian Molinaro:
Explanations for Inconsistency-Tolerant Query Answering under Existential Rules. SEBD 2022: 489-496 - [c185]Thomas Lukasiewicz, Enrico Malizia, Andrius Vaicenavicius:
Complexity of Inconsistency-Tolerant Query Answering in Datalog+/- under Cardinality-Based Repairs. SEBD 2022: 530-537 - [i88]Vid Kocijan, Ernest Davis, Thomas Lukasiewicz, Gary Marcus, Leora Morgenstern:
The Defeat of the Winograd Schema Challenge. CoRR abs/2201.02387 (2022) - [i87]Tommaso Salvatori, Luca Pinchetti, Beren Millidge, Yuhang Song, Rafal Bogacz, Thomas Lukasiewicz:
Learning on Arbitrary Graph Topologies via Predictive Coding. CoRR abs/2201.13180 (2022) - [i86]Beren Millidge, Tommaso Salvatori, Yuhang Song, Thomas Lukasiewicz, Rafal Bogacz:
Universal Hopfield Networks: A General Framework for Single-Shot Associative Memory Models. CoRR abs/2202.04557 (2022) - [i85]Beren Millidge, Tommaso Salvatori, Yuhang Song, Rafal Bogacz, Thomas Lukasiewicz:
Predictive Coding: Towards a Future of Deep Learning beyond Backpropagation? CoRR abs/2202.09467 (2022) - [i84]Eleonora Giunchiglia, Mihaela Catalina Stoian, Thomas Lukasiewicz:
Deep Learning with Logical Constraints. CoRR abs/2205.00523 (2022) - [i83]Myeongjun Jang, Frank Mtumbuka, Thomas Lukasiewicz:
Beyond Distributional Hypothesis: Let Language Models Learn Meaning-Text Correspondence. CoRR abs/2205.03815 (2022) - [i82]Yikuan Li, Mohammad Mamouei, Shishir Rao, Abdelaali Hassaïne, Dexter Canoy, Thomas Lukasiewicz, Kazem Rahimi, Gholamreza Salimi Khorshidi:
Clinical outcome prediction under hypothetical interventions - a representation learning framework for counterfactual reasoning. CoRR abs/2205.07234 (2022) - [i81]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. CoRR abs/2206.02629 (2022) - [i80]Jianfeng Wang, Thomas Lukasiewicz:
Rethinking Bayesian Deep Learning Methods for Semi-Supervised Volumetric Medical Image Segmentation. CoRR abs/2206.09293 (2022) - [i79]Jianfeng Wang, Thomas Lukasiewicz, Daniela Massiceti, Xiaolin Hu, Vladimir Pavlovic, Alexandros Neophytou:
NP-Match: When Neural Processes meet Semi-Supervised Learning. CoRR abs/2207.01066 (2022) - [i78]Maxime Kayser, Cornelius Emde, Oana-Maria Camburu, Guy Parsons, Bartlomiej W. Papiez, Thomas Lukasiewicz:
Explaining Chest X-ray Pathologies in Natural Language. CoRR abs/2207.04343 (2022) - [i77]Zihang Xu, Zhenghua Xu, Shuo Zhang, Thomas Lukasiewicz:
PCA: Semi-supervised Segmentation with Patch Confidence Adversarial Training. CoRR abs/2207.11683 (2022) - [i76]Beren Millidge, Yuhang Song, Tommaso Salvatori, Thomas Lukasiewicz, Rafal Bogacz:
A Theoretical Framework for Inference and Learning in Predictive Coding Networks. CoRR abs/2207.12316 (2022) - [i75]Bowen Li, Thomas Lukasiewicz:
Word-Level Fine-Grained Story Visualization. CoRR abs/2208.02341 (2022) - [i74]Bowen Li, Philip H. S. Torr, Thomas Lukasiewicz:
Memory-Driven Text-to-Image Generation. CoRR abs/2208.07022 (2022) - [i73]Bowen Li, Thomas Lukasiewicz:
Lightweight Long-Range Generative Adversarial Networks. CoRR abs/2209.03793 (2022) - [i72]Louis Mahon, Thomas Lukasiewicz:
Efficient Deep Clustering of Human Activities and How to Improve Evaluation. CoRR abs/2209.08335 (2022) - [i71]Eleonora Giunchiglia, Mihaela Catalina Stoian, Salman Khan, Fabio Cuzzolin, Thomas Lukasiewicz:
ROAD-R: The Autonomous Driving Dataset with Logical Requirements. CoRR abs/2210.01597 (2022) - [i70]Lei Sha, Yuhang Song, Yordan Yordanov, Tommaso Salvatori, Thomas Lukasiewicz:
Bird-Eye Transformers for Text Generation Models. CoRR abs/2210.03985 (2022) - [i69]Wenting Xu, Zhenghua Xu, Junyang Chen, Chang Qi, Thomas Lukasiewicz:
Hybrid Reinforced Medical Report Generation with M-Linear Attention and Repetition Penalty. CoRR abs/2210.13729 (2022) - [i68]Luca Pinchetti, Tommaso Salvatori, Yordan Yordanov, Beren Millidge, Yuhang Song, Thomas Lukasiewicz:
Predictive Coding beyond Gaussian Distributions. CoRR abs/2211.03481 (2022) - [i67]Bowen Li, Thomas Lukasiewicz:
Learning to Model Multimodal Semantic Alignment for Story Visualization. CoRR abs/2211.07289 (2022) - [i66]Tommaso Salvatori, Yuhang Song, Beren Millidge, Zhenghua Xu, Lei Sha, Cornelius Emde, Rafal Bogacz, Thomas Lukasiewicz:
Incremental Predictive Coding: A Parallel and Fully Automatic Learning Algorithm. CoRR abs/2212.00720 (2022) - [i65]Billy Byiringiro, Tommaso Salvatori, Thomas Lukasiewicz:
Robust Graph Representation Learning via Predictive Coding. CoRR abs/2212.04656 (2022) - 2021
- [j59]Elvira Amador-Domínguez, Emilio Serrano, Daniel Manrique, Patrick Hohenecker, Thomas Lukasiewicz:
An ontology-based deep learning approach for triple classification with out-of-knowledge-base entities. Inf. Sci. 564: 85-102 (2021) - [j58]Georg Gottlob, André Hernich, Clemens Kupke, Thomas Lukasiewicz:
Stable Model Semantics for Guarded Existential Rules and Description Logics: Decidability and Complexity. J. ACM 68(5): 35:1-35:87 (2021) - [j57]Eleonora Giunchiglia, Thomas Lukasiewicz:
Multi-Label Classification Neural Networks with Hard Logical Constraints. J. Artif. Intell. Res. 72: 759-818 (2021) - [c184]Ismail Ilkan Ceylan, Thomas Lukasiewicz, Enrico Malizia, Cristian Molinaro, Andrius Vaicenavicius:
Preferred Explanations for Ontology-Mediated Queries under Existential Rules. AAAI 2021: 6262-6270 - [c183]Lei Sha, Thomas Lukasiewicz:
Multi-type Disentanglement without Adversarial Training. AAAI 2021: 9515-9523 - [c182]Vid Kocijan, Oana-Maria Camburu, Thomas Lukasiewicz:
The Gap on Gap: Tackling the Problem of Differing Data Distributions in Bias-Measuring Datasets. AAAI 2021: 13180-13188 - [c181]Lei Sha, Oana-Maria Camburu, Thomas Lukasiewicz:
Learning from the Best: Rationalizing Predictions by Adversarial Information Calibration. AAAI 2021: 13771-13779 - [c180]Lei Sha, Patrick Hohenecker, Thomas Lukasiewicz:
Controlling Text Edition by Changing Answers of Specific Questions. ACL/IJCNLP (Findings) 2021: 1288-1299 - [c179]Sai Vidyaranya Nuthalapati, Ramraj Chandradevan, Eleonora Giunchiglia, Bowen Li, Maxime Kayser, Thomas Lukasiewicz, Carl Yang:
Lightweight Visual Question Answering using Scene Graphs. CIKM 2021: 3353-3357 - [c178]Jianfeng Wang, Thomas Lukasiewicz, Xiaolin Hu, Jianfei Cai, Zhenghua Xu:
RSG: A Simple but Effective Module for Learning Imbalanced Datasets. CVPR 2021: 3784-3793 - [c177]Vid Kocijan, Thomas Lukasiewicz:
Knowledge Base Completion Meets Transfer Learning. EMNLP (1) 2021: 6521-6533 - [c176]Maxime Kayser, Oana-Maria Camburu, Leonard Salewski, Cornelius Emde, Virginie Do, Zeynep Akata, Thomas Lukasiewicz:
e-ViL: A Dataset and Benchmark for Natural Language Explanations in Vision-Language Tasks. ICCV 2021: 1224-1234 - [c175]Ralph Abboud, Ismail Ilkan Ceylan, Martin Grohe, Thomas Lukasiewicz:
The Surprising Power of Graph Neural Networks with Random Node Initialization. IJCAI 2021: 2112-2118 - [c174]Louis Mahon, Thomas Lukasiewicz:
Selective Pseudo-Label Clustering. KI 2021: 158-178 - [c173]Tommaso Salvatori, Yuhang Song, Yujian Hong, Lei Sha, Simon Frieder, Zhenghua Xu, Rafal Bogacz, Thomas Lukasiewicz:
Associative Memories via Predictive Coding. NeurIPS 2021: 3874-3886 - [i64]Shishir Rao, Yikuan Li, Rema Ramakrishnan, Abdelaali Hassaïne, Dexter Canoy, John Cleland, Thomas Lukasiewicz, Gholamreza Salimi Khorshidi, Kazem Rahimi:
An explainable Transformer-based deep learning model for the prediction of incident heart failure. CoRR abs/2101.11359 (2021) - [i63]Yikuan Li, Shishir Rao, Mohammad Mamouei, Gholamreza Salimi Khorshidi, Dexter Canoy, Abdelaali Hassaïne, Thomas Lukasiewicz:
Risk factor identification for incident heart failure using neural network distillation and variable selection. CoRR abs/2102.12936 (2021) - [i62]Tommaso Salvatori, Yuhang Song, Thomas Lukasiewicz, Rafal Bogacz, Zhenghua Xu:
Predictive Coding Can Do Exact Backpropagation on Convolutional and Recurrent Neural Networks. CoRR abs/2103.03725 (2021) - [i61]Tommaso Salvatori, Yuhang Song, Thomas Lukasiewicz, Rafal Bogacz, Zhenghua Xu:
Predictive Coding Can Do Exact Backpropagation on Any Neural Network. CoRR abs/2103.04689 (2021) - [i60]Eleonora Giunchiglia, Thomas Lukasiewicz:
Multi-Label Classification Neural Networks with Hard Logical Constraints. CoRR abs/2103.13427 (2021) - [i59]Maxime Kayser, Oana-Maria Camburu, Leonard Salewski, Cornelius Emde, Virginie Do, Zeynep Akata, Thomas Lukasiewicz:
e-ViL: A Dataset and Benchmark for Natural Language Explanations in Vision-Language Tasks. CoRR abs/2105.03761 (2021) - [i58]Lei Sha, Patrick Hohenecker, Thomas Lukasiewicz:
Controlling Text Edition by Changing Answers of Specific Questions. CoRR abs/2105.11018 (2021) - [i57]Jianfeng Wang, Thomas Lukasiewicz, Xiaolin Hu, Jianfei Cai, Zhenghua Xu:
RSG: A Simple but Effective Module for Learning Imbalanced Datasets. CoRR abs/2106.09859 (2021) - [i56]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. CoRR abs/2106.11360 (2021) - [i55]Bodhisattwa Prasad Majumder, Oana-Maria Camburu, Thomas Lukasiewicz, Julian J. McAuley:
Rationale-Inspired Natural Language Explanations with Commonsense. CoRR abs/2106.13876 (2021) - [i54]Louis Mahon, Thomas Lukasiewicz:
Selective Pseudo-label Clustering. CoRR abs/2107.10692 (2021) - [i53]Myeongjun Jang, Deuk Sin Kwon, Thomas Lukasiewicz:
Accurate, yet inconsistent? Consistency Analysis on Language Understanding Models. CoRR abs/2108.06665 (2021) - [i52]Vid Kocijan, Thomas Lukasiewicz:
Knowledge Base Completion Meets Transfer Learning. CoRR abs/2108.13073 (2021) - [i51]Tommaso Salvatori, Yuhang Song, Yujian Hong, Simon Frieder, Lei Sha, Zhenghua Xu, Rafal Bogacz, Thomas Lukasiewicz:
Associative Memories via Predictive Coding. CoRR abs/2109.08063 (2021) - [i50]Myeongjun Jang, Thomas Lukasiewicz:
NoiER: An Approach for Training more Reliable Fine-TunedDownstream Task Models. CoRR abs/2110.02054 (2021) - [i49]Myeongjun Jang, Thomas Lukasiewicz:
Are Training Resources Insufficient? Predict First Then Explain! CoRR abs/2110.02056 (2021) - [i48]Niall Taylor, Lei Sha, Dan W. Joyce, Thomas Lukasiewicz, Alejo J. Nevado-Holgado, Andrey Kormilitzin:
Rationale production to support clinical decision-making. CoRR abs/2111.07611 (2021) - [i47]Yordan Yordanov, Vid Kocijan, Thomas Lukasiewicz, Oana-Maria Camburu:
Few-Shot Out-of-Domain Transfer Learning of Natural Language Explanations. CoRR abs/2112.06204 (2021) - 2020
- [j56]Alberto Finzi, Thomas Lukasiewicz:
Partially observable game-theoretic agent programming in Golog. Int. J. Approx. Reason. 119: 220-241 (2020) - [j55]Patrick Hohenecker, Thomas Lukasiewicz:
Ontology Reasoning with Deep Neural Networks. J. Artif. Intell. Res. 68: 503-540 (2020) - [j54]Vito Walter Anelli, Renato De Leone, Tommaso Di Noia, Thomas Lukasiewicz, Jessica Rosati:
Combining RDF and SPARQL with CP-theories to reason about preferences in a Linked Data setting. Semantic Web 11(3): 391-419 (2020) - [c172]Thomas Lukasiewicz, Enrico Malizia, Cristian Molinaro:
Explanations for Inconsistency-Tolerant Query Answering under Existential Rules. AAAI 2020: 2909-2916 - [c171]Ralph Abboud, Ismail Ilkan Ceylan, Thomas Lukasiewicz:
Learning to Reason: Leveraging Neural Networks for Approximate DNF Counting. AAAI 2020: 3097-3104 - [c170]Yuhang Song, Jianyi Wang, Thomas Lukasiewicz, Zhenghua Xu, Shangtong Zhang, Andrzej Wojcicki, Mai Xu:
Mega-Reward: Achieving Human-Level Play without Extrinsic Rewards. AAAI 2020: 5826-5833 - [c169]Yuhang Song, Andrzej Wojcicki, Thomas Lukasiewicz, Jianyi Wang, Abi Aryan, Zhenghua Xu, Mai Xu, Zihan Ding, Lianlong Wu:
Arena: A General Evaluation Platform and Building Toolkit for Multi-Agent Intelligence. AAAI 2020: 7253-7260 - [c168]Oana-Maria Camburu, Brendan Shillingford, Pasquale Minervini, Thomas Lukasiewicz, Phil Blunsom:
Make Up Your Mind! Adversarial Generation of Inconsistent Natural Language Explanations. ACL 2020: 4157-4165 - [c167]Bowen Li, Xiaojuan Qi, Thomas Lukasiewicz, Philip H. S. Torr:
ManiGAN: Text-Guided Image Manipulation. CVPR 2020: 7877-7886 - [c166]Ismail Ilkan Ceylan, Thomas Lukasiewicz, Enrico Malizia, Andrius Vaicenavicius:
Explanations for Ontology-Mediated Query Answering in Description Logics (Extended Abstract). Description Logics 2020 - [c165]Ismail Ilkan Ceylan, Thomas Lukasiewicz, Enrico Malizia, Andrius Vaicenavicius:
Explanations for Ontology-Mediated Query Answering in Description Logics. ECAI 2020: 672-679 - [c164]Yordan Yordanov, Oana-Maria Camburu, Vid Kocijan, Thomas Lukasiewicz:
Does the Objective Matter? Comparing Training Objectives for Pronoun Resolution. EMNLP (1) 2020: 4963-4969 - [c163]Patrick Hohenecker, Frank Mtumbuka, Vid Kocijan, Thomas Lukasiewicz:
Systematic Comparison of Neural Architectures and Training Approaches for Open Information Extraction. EMNLP (1) 2020: 8554-8565 - [c162]Zhenghua Xu, Di Yuan, Thomas Lukasiewicz, Cheng Chen, Yishu Miao, Guizhi Xu:
Hybrid Deep-Semantic Matrix Factorization for Tag-Aware Personalized Recommendation. ICASSP 2020: 3442-3446 - [c161]Louis Mahon, Eleonora Giunchiglia, Bowen Li, Thomas Lukasiewicz:
Knowledge Graph Extraction from Videos. ICMLA 2020: 25-32 - [c160]Patrick Hohenecker, Thomas Lukasiewicz:
Ontology Reasoning with Deep Neural Networks (Extended Abstract). IJCAI 2020: 5060-5064 - [c159]Alina Petrova, John Armour, Thomas Lukasiewicz:
Extracting Outcomes from Appellate Decisions in US State Courts. JURIX 2020: 133-142 - [c158]Ismail Ilkan Ceylan, Thomas Lukasiewicz, Enrico Malizia, Cristian Molinaro, Andrius Vaicenavicius:
Explanations for Negative Query Answers under Existential Rules. KR 2020: 223-232 - [c157]Yuhang Song, Thomas Lukasiewicz, Zhenghua Xu, Rafal Bogacz:
Can the Brain Do Backpropagation? - Exact Implementation of Backpropagation in Predictive Coding Networks. NeurIPS 2020 - [c156]Ralph Abboud, Ismail Ilkan Ceylan, Thomas Lukasiewicz, Tommaso Salvatori:
BoxE: A Box Embedding Model for Knowledge Base Completion. NeurIPS 2020 - [c155]