| Towards a theory of out-of-distribution learning A Geisa, R Mehta, HS Helm, J Dey, E Eaton, J Dick, CE Priebe, ... arXiv preprint arXiv:2109.14501, 2021 | 13 | 2021 |
| Prospective learning: Back to the future JT Vogelstein, T Verstynen, KP Kording, L Isik, JW Krakauer, ... arXiv e-prints, arXiv: 2201.07372, 2022 | 5 | 2022 |
| Representation ensembling for synergistic lifelong learning with quasilinear complexity JT Vogelstein, J Dey, HS Helm, W LeVine, RD Mehta, TM Tomita, H Xu, ... arXiv preprint arXiv:2004.12908, 2020 | 5 | 2020 |
| Why do networks have inhibitory/negative connections? Q Wang, MA Powell, A Geisa, E Bridgeford, CE Priebe, JT Vogelstein Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 4 | 2023 |
| Inducing a hierarchy for multi-class classification problems HS Helm, W Yang, S Bharadwaj, K Lytvynets, O Riva, C White, A Geisa, ... arXiv preprint arXiv:2102.10263, 2021 | 4 | 2021 |
| A partition-based similarity for classification distributions HS Helm, RD Mehta, B Duderstadt, W Yang, CM White, A Geisa, ... arXiv preprint arXiv:2011.06557, 2020 | 4 | 2020 |
| Out-of-distribution detection using kernel density polytopes J Dey, A De Silva, W LeVine, J Shin, H Xu, A Geisa, T Chu, L Isik, ... arXiv preprint arXiv:2201.13001, 2022 | 2 | 2022 |
| Omnidirectional transfer for quasilinear lifelong learning JT Vogelstein, J Dey, HS Helm, W LeVine, RD Mehta, A Geisa, H Xu, ... arXiv preprint arXiv:2004.12908, 2020 | 2 | 2020 |
| Polarity is all you need to learn and transfer faster Q Wang, MA Powell, A Geisa, EW Bridgeford, JT Vogelstein arXiv preprint arXiv:2303.17589, 2023 | 1 | 2023 |
| Why Do Networks Need Negative Weights? Q Wang, MA Powell, A Geisa, E Bridgeford, JT Vogelstein CoRR, 2022 | 1 | 2022 |
| Deep Discriminative to Kernel Generative Networks for Calibrated Inference J Dey, H Xu, A De Silva, W LeVine, TM Tomita, A Geisa, T Chu, ... | | 2023 |
| Deep discriminative to kernel generative modeling J Dey, W LeVine, A De Silva, A Geisa, JM Shin, H Xu, T Chu, L Isik, ... arXiv preprint arXiv:2201.13001, 2022 | | 2022 |
| Representation Ensembling for Synergistic Lifelong Learning with Quasilinear Complexity J Dey, J Vogelstein, H Helm, W Levine, R Mehta, A Geisa, H Xu, ... | | 2022 |
| Deep Discriminative to Kernel Density Graph for In-and Out-of-distribution Calibrated Inference J Dey, W LeVine, A De Silva, H Xu, TM Tomita, A Geisa, J Desman, ... arXiv preprint arXiv:2201.13001, 2022 | | 2022 |
| Deep Discriminative to Kernel Density Networks for Calibrated Inference J Dey, W LeVine, H Xu, A De Silva, TM Tomita, A Geisa, T Chu, J Desman, ... arXiv preprint arXiv:2201.13001, 2022 | | 2022 |
| Omnidirectional Transfer for Quasilinear Lifelong Learning J Dey, J Vogelstein, H Helm, W Levine, R Mehta, A Geisa, G de Ven, ... | | 2021 |
