| Invariant Information Clustering for Unsupervised Image Classification and Segmentation X Ji, JF Henriques, A Vedaldi arXiv preprint arXiv:1807.06653, 2019 | 1161 | 2019 |
| Consciousness in artificial intelligence: insights from the science of consciousness P Butlin, R Long, E Elmoznino, Y Bengio, J Birch, A Constant, G Deane, ... arXiv preprint arXiv:2308.08708, 2023 | 166 | 2023 |
| There and back again: Revisiting backpropagation saliency methods SA Rebuffi, R Fong, X Ji, A Vedaldi Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 146 | 2020 |
| GFlowNets and variational inference N Malkin, S Lahlou, T Deleu, X Ji, E Hu, K Everett, D Zhang, Y Bengio arXiv preprint arXiv:2210.00580, 2022 | 89 | 2022 |
| How does information bottleneck help deep learning? K Kawaguchi, Z Deng, X Ji, J Huang International Conference on Machine Learning, 16049-16096, 2023 | 74 | 2023 |
| Gflowout: Dropout with generative flow networks D Liu, M Jain, BFP Dossou, Q Shen, S Lahlou, A Goyal, N Malkin, ... International Conference on Machine Learning, 21715-21729, 2023 | 23 | 2023 |
| On the role of neurogenesis in overcoming catastrophic forgetting GI Parisi, X Ji, S Wermter arXiv preprint arXiv:1811.02113, 2018 | 19 | 2018 |
| Sources of richness and ineffability for phenomenally conscious states X Ji, E Elmoznino, G Deane, A Constant, G Dumas, G Lajoie, J Simon, ... Neuroscience of Consciousness 2024 (1), niae001, 2024 | 15 | 2024 |
| Adaptive discrete communication bottlenecks with dynamic vector quantization for heterogeneous representational coarseness D Liu, A Lamb, X Ji, PJT Notsawo, M Mozer, Y Bengio, K Kawaguchi Proceedings of the AAAI Conference on Artificial Intelligence 37 (7), 8825-8833, 2023 | 15 | 2023 |
| Automatic recall machines: Internal replay, continual learning and the brain X Ji, J Henriques, T Tuytelaars, A Vedaldi arXiv preprint arXiv:2006.12323, 2020 | 15 | 2020 |
| Consciousness in artificial intelligence: Insights from the science of consciousness (arXiv: 2308.08708). arXiv P Butlin, R Long, E Elmoznino, Y Bengio, J Birch, A Constant, G Deane, ... | 13 | 2023 |
| Test Sample Accuracy Scales with Training Sample Density in Neural Networks X Ji, R Pascanu, D Hjelm, B Lakshminarayanan, A Vedaldi arXiv preprint arXiv:2106.08365, 2021 | 11* | 2021 |
| Graph-Based Active Machine Learning Method for Diverse and Novel Antimicrobial Peptides Generation and Selection BFP Dossou, D Liu, X Ji, M Jain, AM van der Sloot, R Palou, M Tyers, ... arXiv preprint arXiv:2209.13518, 2022 | 1 | 2022 |
| Properties of minimizing entropy X Ji, L Nehale-Ezzine, M Korablyov arXiv preprint arXiv:2112.03143, 2021 | 1 | 2021 |
| Unsupervised learning and continual learning in neural networks X Ji University of Oxford, 2021 | 1 | 2021 |
| Deep learning predicts onset acceleration of 38 age-associated diseases from blood and body composition biomarkers in the UK Biobank MX Ji, M Thanaj, L Nehale-Ezzine, B Whitcher, EL Thomas, JD Bell medRxiv preprint medRxiv:2025.03.16.25323714, 2025 | | 2025 |
| La Conciencia en la Inteligencia Artificial: Reflexiones desde la Ciencia de la Conciencia P Butlin, R Long, E Elmoznino, Y Bengio, J Birch, A Constant, G Deane, ... | | |
| An Analysis of Information Bottlenecks K Kawaguchi, X Ji, J Huang, Y Bengio | | |
