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2020 – today
- 2024
[i4]Jifan Zhang, Lalit Jain, Yang Guo, Jiayi Chen, Kuan Lok Zhou, Siddharth Suresh, Andrew Wagenmaker, Scott Sievert, Timothy T. Rogers, Kevin Jamieson, Robert Mankoff, Robert Nowak:
Humor in AI: Massive Scale Crowd-Sourced Preferences and Benchmarks for Cartoon Captioning. CoRR abs/2406.10522 (2024)- 2023
- [j2]Scott Sievert
, Robert D. Nowak, Timothy T. Rogers:
Efficiently Learning Relative Similarity Embeddings with Crowdsourcing. J. Open Source Softw. 8(83): 4517 (2023) - 2022
- [c5]Kyumin Lee, Guanyi Mou, Scott Sievert:
Energy-based Domain Adaption with Active Learning for Emerging Misinformation Detection. IEEE Big Data 2022: 2305-2308 - 2021
- [c4]Joesph Holt, Scott Sievert:
Training machine learning models faster with Dask. SciPy 2021: 132-139
2010 – 2019
- 2019
- [c3]Scott Sievert, Tom Augspurger, Matthew Rocklin:
Better and faster hyperparameter optimization with Dask. SciPy 2019: 118-125 - [i3]Scott Sievert, Zachary Charles:
Improving the convergence of SGD through adaptive batch sizes. CoRR abs/1910.08222 (2019) - 2018
- [j1]Jacob VanderPlas, Brian E. Granger, Jeffrey Heer, Dominik Moritz, Kanit Wongsuphasawat, Arvind Satyanarayan, Eitan Lees, Ilia Timofeev, Ben Welsh, Scott Sievert:
Altair: Interactive Statistical Visualizations for Python. J. Open Source Softw. 3(32): 1057 (2018) - [c2]Hongyi Wang, Scott Sievert, Shengchao Liu, Zachary Charles, Dimitris S. Papailiopoulos, Stephen J. Wright:
ATOMO: Communication-efficient Learning via Atomic Sparsification. NeurIPS 2018: 9872-9883 - [d2]Jacob VanderPlas, Brian E. Granger, Jeffrey Heer, Dominik Moritz, Kanit Wongsuphasawat, Eitan Lees, Ilia Timofeev, Ben Welsh, Scott Sievert:
Altair: Declarative statistical visualization library for Python. Version 2. Zenodo, 2018 [all versions]
- [d1]Jacob VanderPlas, Brian E. Granger, Jeffrey Heer, Dominik Moritz, Kanit Wongsuphasawat, Arvind Satyanarayan, Eitan Lees, Ilia Timofeev, Ben Welsh, Scott Sievert:
Altair: Declarative statistical visualization library for Python. Version 2.3. Zenodo, 2018 [all versions] - [i2]Hongyi Wang, Scott Sievert, Shengchao Liu, Zachary Charles, Dimitris S. Papailiopoulos, Stephen J. Wright:
ATOMO: Communication-efficient Learning via Atomic Sparsification. CoRR abs/1806.04090 (2018) - 2017
- [c1]Scott Sievert, Daniel Ross, Lalit Jain, Kevin Jamieson, Robert Nowak, Robert Mankoff:
NEXT: A system to easily connect crowdsourcing and adaptive data collection. SciPy 2017: 113-119 - 2015
- [i1]Michael R. Crusoe, Hussien F. Alameldin, Sherine Awad, Elmar Boucher, Adam Caldwell, Reed Cartwright, Amanda Charbonneau, Bede Constantinides, Greg Edvenson, Scott Fay, Jacob Fenton, Thomas Fenzl, Jordan A. Fish, Leonor Garcia-Gutierrez, Phillip Garland, Jonathan Gluck, Iván González, Sarah Guermond, Jiarong Guo, Aditi Gupta, Joshua R. Herr, Adina Howe, Alex Hyer, Andreas Härpfer, Luiz Irber, Rhys Kidd, David Lin, Justin Lippi, Tamer A. Mansour, Pamela McA'Nulty, Eric McDonald, Jessica Mizzi, Kevin D. Murray, Joshua R. Nahum, Kaben Nanlohy, Alexander Johan Nederbragt, Humberto Ortiz-Zuazaga, Jeramia Ory, Jason Pell, Charles Pepe-Ranney, Zachary N. Russ, Erich M. Schwarz, Camille Scott, Josiah D. Seaman, Scott Sievert, Jared Simpson, Connor Skennerton, James Spencer, Ramakrishnan Srinivasan, Daniel S. Standage, James A. Stapleton, Susan R. Steinman, Joe Stein, Benjamin Taylor, Will Trimble, Heather Wiencko, Michael Wright, Brian Wyss, Qingpeng Zhang, en zyme, C. Titus Brown:
The khmer software package: enabling efficient nucleotide sequence analysis. F1000Research 4: 900 (2015)
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