Katedra Uczenia Maszynowego - lista publikacji

Supermodeling: the next level of abstraction in the use of data assimilation, International Conference on Computational Science [ICCS] vol. vol. Lecture Notes in Computer Science book series (LNCS, vol. 12142) (2020), 133-147

Emulating docking results using a deep neural network: a new perspective for virtual screening, Journal of Chemical Information and Modeling (2020), 4246-4262

Plugin Networks for Inference under Partial Evidence, IEEE Workshop on Applications of Computer Vision [WACV], (2020),

The importance of standardisation – COVID-19 CT & Radiograph Image Data Stock for deep learning purpose, Computers in Biology and Medicine vol. 127 (2020), 104092

Fast and Stable Interval Bounds Propagation for Training Verifiably Robust Models, European Symposium on Artificial Neural Networks [ESANN], (2020), 6

Estimating conditional density of missing values using deep Gaussian mixture model, International Conference on Neural Information Processing [ICONIP] vol. Lecture Notes in Computer Science volume 12534 (2020), 220-231

Iterative Imputation of Missing Data using Auto-encoder Dynamics, International Conference on Neural Information Processing [ICONIP] vol. Lecture Notes in Computer Science, volume 12534 (2020), 258-269

Processing of Incomplete Images by (Graph) Convolutional Neural Networks, International Conference On Neural Information Processing vol. Lecture Notes in Computer Science, volume 12533 (2020), 512-523

Spatial Graph Convolutional Networks, International Conference On Neural Information Processing vol. Communications in Computer and Information Science book series (CCIS, volume 1333) (2020), 668-675

Non-linear ICA based on Cramer-Wold metric, International Conference On Neural Information Processing vol. Lecture Notes in Computer Science book series (LNCS, volume 12534) (2020),

Simulation-Based Reinforcement Learning for Real-World Autonomous Driving, IEEE International Conference on Robotics and Automation [ICRA], (2020), 6411-6418

Hypernetwork approach to generating point clouds, International Conference on Machine Learning [ICML](MAIN), (2020),

Classifier-agnostic saliency map extraction, Computer Vision and Image Understanding (2020),

Combating False Negatives in Adversarial Imitation Learning, National Conference of the American Association for Artificial Intelligence [AAAI], (2020), 13999-14000

Leakage-Robust Classifier via Mask-Enhanced Training, National Conference of the American Association for Artificial Intelligence [AAAI], (2020), 13923-13924

Can auto-encoders help with filling missing data?, International Conference On Learning Represenation (workshop Track) (2020), 6

Estimating conditional density of missing values using deep Gaussian mixture model, International Conference On Machine Learning (workshop Track) (2020), 6

From Dataset Recycling to Multi-Property Extraction and Beyond, Conference on Computational Natural Language Learning [CoNLL] vol. Proceedings of the 24th Conference on Computational Natural Language Learning (2020),

Finding the Optimal Network Depth in Classification Tasks, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Database (PKDD and ECML combined from 2008) [ECML PKDD], (2020),

The Break-Even Point on Optimization Trajectories of Deep Neural Networks, 8th International Conference On Learning Representations (2020),

Emulating Docking Results Using a Deep Neural Network: A New Perspective for Virtual Screening, Journal of Chemical Information and Modeling vol. 60 (2020), 4246-4262

Google Research Football: A Novel Reinforcement Learning Environment, Proceedings of the Aaai Conference On Artificial Intelligence vol. Vol 34 No 04 (2020), 4501-4510

Cramer-Wold Auto-Encoder, Journal of Machine Learning Research vol. 21 (2020), 1-28

Processing of incomplete images by (graph) convolutional neural networks, International Conference On Machine Learning (workshop Track) (2020),

Flow-based SVDD for anomaly detection, International Conference On Machine Learning (workshop Track) (2020),

Deep learning approach to describe and classify fungi microscopic images, PLoS One vol. 15(6) (2020), 1-16

Securing Data of Biotechnological Laboratories Using Blockchain Technology, Lecture Notes in Computer Science vol. 12133 (2020),

A Classification-Based Approach to Semi-Supervised Clustering with Pairwise Constraints, Neural Networks vol. 127 (2020), 193-203

How Sure Can We Be about ML Methods-Based Evaluation of Compound Activity: Incorporation of Information about Prediction Uncertainty Using Deep Learning Techniques, Molecules (2020),

Mol-CycleGAN: a generative model for molecular optimization, Journal of Cheminformatics vol. 12 (2020),

Pointed subspace approach to incomplete data, Journal of Classification vol. 37 (2020), 42-57