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2020 – today
- 2023
[j11]David Rolnick, Priya L. Donti, Lynn H. Kaack, Kelly Kochanski, Alexandre Lacoste, Kris Sankaran, Andrew Slavin Ross, Nikola Milojevic-Dupont, Natasha Jaques, Anna Waldman-Brown, Alexandra Sasha Luccioni, Tegan Maharaj, Evan D. Sherwin, S. Karthik Mukkavilli, Konrad P. Kording, Carla P. Gomes, Andrew Y. Ng, Demis Hassabis, John C. Platt, Felix Creutzig, Jennifer T. Chayes, Yoshua Bengio:
Tackling Climate Change with Machine Learning. ACM Comput. Surv. 55(2): 42:1-42:96 (2023)- 2022
- [i24]Gabriel Tseng, Hannah Kerner, David Rolnick:
TIML: Task-Informed Meta-Learning for Agriculture. CoRR abs/2202.02124 (2022) - [i23]Richard D. Lange, David S. Rolnick, Konrad P. Kording:
Clustering units in neural networks: upstream vs downstream information. CoRR abs/2203.11815 (2022) - 2021
- [j10]Christopher Hillar, Tenzin Chan, Rachel Taubman, David Rolnick:
Hidden Hypergraphs, Error-Correcting Codes, and Critical Learning in Hopfield Networks. Entropy 23(11): 1494 (2021) - [c14]Priya L. Donti, David Rolnick, J. Zico Kolter:
DC3: A learning method for optimization with hard constraints. ICLR 2021 - [c13]Salva Rühling Cachay, Venkatesh Ramesh, Jason N. S. Cole, Howard Barker, David Rolnick:
ClimART: A Benchmark Dataset for Emulating Atmospheric Radiative Transfer in Weather and Climate Models. NeurIPS Datasets and Benchmarks 2021 - [c12]Sever Topan, David Rolnick, Xujie Si:
Techniques for Symbol Grounding with SATNet. NeurIPS 2021: 20733-20744 - [i22]Boris Hanin, Ryan Jeong, David Rolnick:
Deep ReLU Networks Preserve Expected Length. CoRR abs/2102.10492 (2021) - [i21]Charles A. Kantor, Marta Skreta, Brice Rauby, Léonard Boussioux, Emmanuel Jehanno, Alexandra Luccioni, David Rolnick, Hugues Talbot:
Geo-Spatiotemporal Features and Shape-Based Prior Knowledge for Fine-grained Imbalanced Data Classification. CoRR abs/2103.11285 (2021) - [i20]Priya L. Donti, David Rolnick, J. Zico Kolter:
DC3: A learning method for optimization with hard constraints. CoRR abs/2104.12225 (2021) - [i19]Sever Topan, David Rolnick, Xujie Si:
Techniques for Symbol Grounding with SATNet. CoRR abs/2106.11072 (2021) - [i18]Salva Rühling Cachay, Venkatesh Ramesh, Jason N. S. Cole, Howard Barker, David Rolnick:
ClimART: A Benchmark Dataset for Emulating Atmospheric Radiative Transfer in Weather and Climate Models. CoRR abs/2111.14671 (2021) - 2020
- [c11]David Rolnick, Konrad P. Kording:
Reverse-engineering deep ReLU networks. ICML 2020: 8178-8187
2010 – 2019
- 2019
- [c10]Yaron Meirovitch, Lu Mi, Hayk Saribekyan, Alexander Matveev, David Rolnick, Nir Shavit:
Cross-Classification Clustering: An Efficient Multi-Object Tracking Technique for 3-D Instance Segmentation in Connectomics. CVPR 2019: 8425-8435 - [c9]Ari S. Benjamin, David Rolnick, Konrad P. Körding:
Measuring and regularizing networks in function space. ICLR (Poster) 2019 - [c8]Boris Hanin, David Rolnick:
Complexity of Linear Regions in Deep Networks. ICML 2019: 2596-2604 - [c7]David Rolnick, Kevin Aydin, Jean Pouget-Abadie, Shahab Kamali, Vahab S. Mirrokni, Amir Najmi:
Randomized Experimental Design via Geographic Clustering. KDD 2019: 2745-2753 - [c6]David Rolnick, Arun Ahuja, Jonathan Schwarz, Timothy P. Lillicrap, Gregory Wayne:
Experience Replay for Continual Learning. NeurIPS 2019: 348-358 - [c5]Boris Hanin, David Rolnick:
Deep ReLU Networks Have Surprisingly Few Activation Patterns. NeurIPS 2019: 359-368 - [i17]Boris Hanin, David Rolnick:
Complexity of Linear Regions in Deep Networks. CoRR abs/1901.09021 (2019) - [i16]Boris Hanin, David Rolnick:
Deep ReLU Networks Have Surprisingly Few Activation Patterns. CoRR abs/1906.00904 (2019) - [i15]David Rolnick, Priya L. Donti, Lynn H. Kaack, Kelly Kochanski, Alexandre Lacoste, Kris Sankaran, Andrew Slavin Ross, Nikola Milojevic-Dupont, Natasha Jaques, Anna Waldman-Brown, Alexandra Luccioni, Tegan Maharaj, Evan D. Sherwin, S. Karthik Mukkavilli
, Konrad P. Körding, Carla P. Gomes, Andrew Y. Ng, Demis Hassabis, John C. Platt, Felix Creutzig, Jennifer T. Chayes, Yoshua Bengio:
Tackling Climate Change with Machine Learning. CoRR abs/1906.05433 (2019) - [i14]David Rolnick, Konrad P. Körding:
Identifying Weights and Architectures of Unknown ReLU Networks. CoRR abs/1910.00744 (2019) - 2018
- [c4]David Rolnick, Max Tegmark:
The power of deeper networks for expressing natural functions. ICLR (Poster) 2018 - [c3]Boris Hanin, David Rolnick:
How to Start Training: The Effect of Initialization and Architecture. NeurIPS 2018: 569-579 - [i13]Boris Hanin, David Rolnick:
How to Start Training: The Effect of Initialization and Architecture. CoRR abs/1803.01719 (2018) - [i12]Ari S. Benjamin, David Rolnick, Konrad P. Körding:
Measuring and regularizing networks in function space. CoRR abs/1805.08289 (2018) - [i11]David Rolnick, Arun Ahuja, Jonathan Schwarz, Timothy P. Lillicrap, Greg Wayne:
Experience Replay for Continual Learning. CoRR abs/1811.11682 (2018) - [i10]Yaron Meirovitch, Lu Mi, Hayk Saribekyan, Alexander Matveev, David Rolnick, Casimir Wierzynski, Nir Shavit:
Cross-Classification Clustering: An Efficient Multi-Object Tracking Technique for 3-D Instance Segmentation in Connectomics. CoRR abs/1812.01157 (2018) - 2017
- [j9]Jesús A. De Loera, Reuben N. La Haye, David Rolnick, Pablo Soberón:
Quantitative Combinatorial Geometry for Continuous Parameters. Discret. Comput. Geom. 57(2): 318-334 (2017) - [j8]Jesús A. De Loera, Reuben N. La Haye, David Rolnick, Pablo Soberón:
Quantitative Tverberg Theorems Over Lattices and Other Discrete Sets. Discret. Comput. Geom. 58(2): 435-448 (2017) - [j7]David Rolnick, Pablo Soberón:
Quantitative (p, q) theorems in combinatorial geometry. Discret. Math. 340(10): 2516-2527 (2017) - [j6]David Rolnick:
On the classification of Stanley sequences. Eur. J. Comb. 59: 51-70 (2017) - [c2]Jeremy Bernstein, Ishita Dasgupta, David Rolnick, Haim Sompolinsky:
Markov Transitions between Attractor States in a Recurrent Neural Network. AAAI Spring Symposia 2017 - [i9]David Rolnick, Max Tegmark:
The power of deeper networks for expressing natural functions. CoRR abs/1705.05502 (2017) - [i8]David Rolnick, Andreas Veit, Serge J. Belongie, Nir Shavit:
Deep Learning is Robust to Massive Label Noise. CoRR abs/1705.10694 (2017) - [i7]David Rolnick, Yaron Meirovitch, Toufiq Parag, Hanspeter Pfister, Viren Jain, Jeff W. Lichtman, Edward S. Boyden, Nir Shavit:
Morphological Error Detection in 3D Segmentations. CoRR abs/1705.10882 (2017) - 2016
- [j5]Richard A. Moy, David Rolnick:
Novel structures in Stanley sequences. Discret. Math. 339(2): 689-698 (2016) - [i6]David Rolnick, Pablo Soberón:
Algorithmic aspects of Tverberg's Theorem. CoRR abs/1601.03083 (2016) - [i5]David Rolnick, Kevin Aydin, Shahab Kamali, Vahab S. Mirrokni, Amir Najmi:
GeoCUTS: Geographic Clustering Using Travel Statistics. CoRR abs/1611.03780 (2016) - [i4]Yaron Meirovitch, Alexander Matveev, Hayk Saribekyan, David M. Budden, David Rolnick, Gergely Ódor, Seymour Knowles-Barley, Thouis Raymond Jones, Hanspeter Pfister, Jeff William Lichtman, Nir Shavit:
A Multi-Pass Approach to Large-Scale Connectomics. CoRR abs/1612.02120 (2016) - 2015
- [j4]Noah Golowich, David Rolnick:
Acyclic Subgraphs of Planar Digraphs. Electron. J. Comb. 22(3): P3.7 (2015) - [j3]David Rolnick, Praveen S. Venkataramana:
On the growth of Stanley sequences. Discret. Math. 338(11): 1928-1937 (2015) - [c1]Jesús A. De Loera, Susan Margulies, Michael Pernpeintner, Eric Riedl, David Rolnick, Gwen Spencer, Despina Stasi, Jon Swenson:
Graph-Coloring Ideals: Nullstellensatz Certificates, Gröbner Bases for Chordal Graphs, and Hardness of Gröbner Bases. ISSAC 2015: 133-140 - [i3]Richard A. Moy, David Rolnick:
Novel structures in Stanley sequences. CoRR abs/1502.06013 (2015) - [i2]Gwen Spencer, David Rolnick:
On the robust hardness of Gröbner basis computation. CoRR abs/1511.06436 (2015) - 2014
- [i1]Jesús A. De Loera, Susan Margulies, Michael Pernpeintner, Eric Riedl, David Rolnick, Gwen Spencer, Despina Stasi, Jon Swenson:
Gröbner Bases and Nullstellensätze for Graph-Coloring Ideals. CoRR abs/1410.6806 (2014) - 2013
- [j2]David Rolnick:
The on-line degree Ramsey number of cycles. Discret. Math. 313(20): 2084-2093 (2013) - 2011
- [j1]David Rolnick:
Trees with an On-Line Degree Ramsey Number of Four. Electron. J. Comb. 18(1) (2011)
Coauthor Index
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