| Disruption of ecological networks in lakes by climate change and nutrient fluctuations E Merz, E Saberski, LJ Gilarranz, PDF Isles, G Sugihara, C Berger, ... Nature Climate Change 13 (4), 389-396, 2023 | 42 | 2023 |
| Human visual consciousness involves large scale cortical and subcortical networks independent of task report and eye movement activity SI Kronemer, M Aksen, JZ Ding, JH Ryu, Q Xin, Z Ding, JS Prince, H Kwon, ... Nature Communications 13 (1), 7342, 2022 | 37 | 2022 |
| Networks of causal linkage between eigenmodes characterize behavioral dynamics of caenorhabditis elegans E Saberski, AK Bock, R Goodridge, V Agarwal, T Lorimer, SA Rifkin, ... PLoS computational biology 17 (9), e1009329, 2021 | 9 | 2021 |
| Brain networks in human conscious visual perception SI Kronemer, M Aksen, J Ding, JH Ryu, Q Xin, Z Ding, JS Prince, H Kwon, ... BioRxiv, 2021.10. 04.462661, 2021 | 7 | 2021 |
| Empirical dynamic modeling G Sugihara, J Park, E Deyle, E Saberski, C Smith, H Ye The Comprehensive R Archive Network. Tomaru, T., Murakami, H., Niizato, T …, 2020 | 7 | 2020 |
| rEDM: an R package for empirical dynamic modeling and convergent cross mapping G Sugihara, H Ye, A Clark, E Deyle SERDP, 2019 | 7 | 2019 |
| Discovery and dynamics of a cryptic marine copepod-parasite interaction EC Orenstein, E Saberski, C Briseño-Avena Marine Ecology Progress Series 691, 29-40, 2022 | 6 | 2022 |
| Circularity in fisheries data weakens real world prediction A Giron-Nava, SB Munch, AF Johnson, E Deyle, CC James, E Saberski, ... Scientific reports 10 (1), 6977, 2020 | 6 | 2020 |
| Improved prediction of managed water flow into Everglades National Park using empirical dynamic modeling E Saberski, J Park, T Hill, E Stabenau, G Sugihara Journal of Water Resources Planning and Management 148 (12), 05022009, 2022 | 5 | 2022 |
| Tracking changes in behavioural dynamics using prediction error T Lorimer, R Goodridge, AK Bock, V Agarwal, E Saberski, G Sugihara, ... Plos one 16 (5), e0251053, 2021 | 5 | 2021 |
| Comprehensive incentives for reducing Chinook salmon bycatch in the Bering Sea walleye pollock fishery: individual tradable encounter credits G Sugihara, KR Criddle, M McQuown, A Giron-Nava, E Deyle, C James, ... Regional Studies in Marine Science 22, 70-81, 2018 | 4 | 2018 |
| Post-reproductive parthenogenetic pea aphids (Acyrthosiphon pisum) are visually identifiable and disproportionately positioned distally to clonal colonies ET Saberski, JD Diamond, NF Henneman, DA Levitis PeerJ 4, e2631, 2016 | 3 | 2016 |
| Dynamics of Florida milk production and total phosphate in Lake Okeechobee J Park, E Saberski, E Stabenau, G Sugihara Plos one 16 (8), e0248910, 2021 | 2 | 2021 |
| Temperature triggers provide quantitative predictions of multi-species fish spawning peaks ES Choi, ET Saberski, T Lorimer, C Smith, U Kandage-don, RS Burton, ... bioRxiv, 2020.07. 10.196923, 2020 | 1 | 2020 |
| The impact of data resolution on dynamic causal inference in multiscale ecological networks E Saberski, T Lorimer, D Carpenter, E Deyle, E Merz, J Park, GM Pao, ... Communications Biology 7 (1), 1442, 2024 | | 2024 |
| Stress Drives Soccer Athletes’ Wellness and Movement: Using Convergent Cross-Mapping to Identify Causal Relationships in a Dynamic Environment BD Stern, ER Deyle, EJ Hegedus, SB Munch, E Saberski International Journal of Sports Physiology and Performance 19 (10), 1030-1040, 2024 | | 2024 |
| Specific Solutions to General Problems in Data Science and Ecology E Saberski UC San Diego, 2024 | | 2024 |
| Recovering High-Frequency Plankton Dynamics from Low-Frequency Samples G Sugihara, D Carpenter, E Saberski AGU Fall Meeting Abstracts 2023 (628), NG21B-0628, 2023 | | 2023 |
| Quantifying Dynamics Across Scales Through Data-Driven Analysis E Saberski, G Sugihara, D Carpenter AGU Fall Meeting Abstracts 2023 (626), NG21B-0626, 2023 | | 2023 |
| Navigating a World where Causes are Invisible G Sugihara, E Saberski, D Carpenter AGU Fall Meeting Abstracts 2023, NG14A-01, 2023 | | 2023 |
