| Uncertainty estimations by softplus normalization in Bayesian convolutional neural networks with variational inference K Shridhar, F Laumann, M Liwicki 10th International Workshop on Simulation and Statistics, 2019 | 89 | 2019 |
| Complex interlinkages, key objectives, and nexuses among the Sustainable Development Goals and climate change: a network analysis F Laumann, J von Kügelgen, THK Uehara, M Barahona The Lancet Planetary Health 6 (5), e422-e430, 2022 | 67 | 2022 |
| Indic-transformers: An analysis of transformer language models for indian languages K Jain, A Deshpande, K Shridhar, F Laumann, A Dash arXiv preprint arXiv:2011.02323, 2020 | 50 | 2020 |
| Enterprise architecture for a facilitated transformation from a linear to a circular economy F Laumann, T Tambo Sustainability 10 (11), 3882, 2018 | 33 | 2018 |
| Energy harvesting through piezoelectricity - technology foresight F Laumann, M Møller Sørensen, RF Jul Lindemann, T Mølholm Hansen, ... Energy Procedia 142, 3062-3068, 2017 | 24 | 2017 |
| One to rule them all: Towards joint indic language hate speech detection M Bhatia, TS Bhotia, A Agarwal, P Ramesh, S Gupta, K Shridhar, ... arXiv preprint arXiv:2109.13711, 2021 | 20 | 2021 |
| A hybrid approach to identifying and assessing interactions between climate action (SDG13) policies and a range of SDGs in a UK context S Stevenson, A Collins, N Jennings, AC Köberle, F Laumann, AA Laverty, ... Discover Sustainability 2 (1), 43, 2021 | 14 | 2021 |
| The neuron mixer and its impact on human brain dynamics CE Luff, R Peach, EJ Mallas, E Rhodes, F Laumann, ES Boyden, ... Cell Reports 43 (6), 2024 | 12 | 2024 |
| Kernel-based independence tests for causal structure learning on functional data F Laumann, J Von Kügelgen, J Park, B Schölkopf, M Barahona Entropy 25 (12), 1597, 2023 | 10 | 2023 |
| Kernel Two-Sample and Independence Tests for Non-Stationary Random Processes F Laumann, J von Kügelgen, M Barahona Engineering Proceedings 5 (1), 2021 | 6 | 2021 |
| Kernel-based joint independence tests for multivariate stationary and non-stationary time series Z Liu, RL Peach, F Laumann, S Vallejo Mengod, M Barahona Royal Society Open Science 10 (11), 230857, 2023 | 3 | 2023 |
| A continuous structural intervention distance to compare causal graphs M Dhanakshirur, F Laumann, J Park, M Barahona In: Zhou, XH., Jia, J. (eds) Causal Inference. PCIC 2024. Communications in …, 2023 | 3 | 2023 |
| Non-linear interlinkages and key objectives amongst the Paris Agreement and the Sustainable Development Goals F Laumann, J von Kügelgen, M Barahona ICLR 2020 Workshop 'Tackling Climate Change with Machine Learning', 2020 | 3 | 2020 |
| Enterprise architecture for a facilitated transformation from a linear to a circular economy. Sustainability, 10., 3882 F Laumann, T Tambo | 2 | 2018 |
| Bayesian transfer learning for deep networks J Wohlert, A Munk, S Sengupta, F Laumann ViXra, 2018 | 2 | 2018 |
| Complex interlinkages between the SDGs and their importance to African development MV Faul, F Laumann | 1 | 2024 |
| Complex interlinkages, key objectives, and nexuses among the Sustainable Development Goals and climate change: a network analysis (vol 6, e422, 2022) F Laumann, J von Kügelgen, KTH Uehara, M Barahona LANCET PLANETARY HEALTH 6 (8), E644-E644, 2022 | 1 | 2022 |
| Bayesian convolutional neural network K Shridhar University of Kaiserslautern, 2019 | 1 | 2019 |
| Correction to Lancet Planet Health 2022; 6: e422–30 F Laumann, J von Kügelgen, TH Kanashiro Uehara, M Barahona, J Liu, ... | | 2022 |
| Discover Sustainability S Stevenson, A Collins, N Jennings, AC Köberle, F Laumann, AA Laverty, ... | | 2021 |
Mauricio BarahonaImperial College London, Applied Mathematics, Chair in BiomathematicsVerified email at imperial.ac.uk
