David Rolnick
30 papers · 2018–2026 · 7 conferences · across top CS/AI conferences
Achievements
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๐ Conference Polyglot (7) ๐ Academic Marathon (7) ๐ Interdisciplinary Bridge ๐งญ Keyword Pioneer ๐ Cross-Pollinator (7)
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Cross-Pollinator
(7)
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Renaissance Researcher
(7)
๐บ๏ธ
Taxonomy Completionist
(48)
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Triple Crown
๐ฅ
Mega-Team
(28)
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Keyword Champion
(2)
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Grand Slam
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Century Club
(29)
๐๏ธ
Keyword Collector
(106)
๐ฅ
Unstoppable
(8)
โก
Prolific Year
(5)
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Conference Pioneer
Conferences
ICML (10)
NIPS (8)
ICLR (4)
AAAI (3)
JMLR (3)
CVPR (1)
ECCV (1)
Top co-authors
Keywords
relu network
(5)
remote sensing
(2)
linear region
(2)
network architecture
(2)
piecewise linear function
(2)
graph neural network
(2)
multi-task learning
(1)
catastrophic forgetting
(1)
image classification
(1)
domain adaptation
(1)
uncertainty quantification
(1)
epistemic uncertainty
(1)
logical reasoning
(1)
self-supervised learning
(1)
transfer learning
(1)
continual learning
(1)
instance segmentation
(1)
visual reasoning
(1)
neural network interpretability
(1)
policy learning
(1)
Papers
BATIS: Bayesian Approaches for Targeted Improvement of Species Distribution Models
AAAI 2026
Galileo: Learning Global & Local Features of Many Remote Sensing Modalities
ICML 2025
Alberta Wells Dataset: Pinpointing Oil and Gas Wells from Satellite Imagery
ICML 2025
The Butterfly Effect: Neural Network Training Trajectories Are Highly Sensitive to Initial Conditions
ICML 2025
FoMo: Multi-Modal, Multi-Scale and Multi-Task Remote Sensing Foundation Models for Forest Monitoring
AAAI 2025
Position: Application-Driven Innovation in Machine Learning
ICML 2024
Insect Identification in the Wild: The AMI Dataset
ECCV 2024
PhAST: Physics-Aware, Scalable, and Task-Specific GNNs for Accelerated Catalyst Design
JMLR 2024
Stealing part of a production language model
ICML 2024
Fourier Neural Operators for Arbitrary Resolution Climate Data Downscaling
JMLR 2024
Maximal Initial Learning Rates in Deep ReLU Networks
ICML 2023
Hidden Symmetries of ReLU Networks
ICML 2023
ClimateSet: A Large-Scale Climate Model Dataset for Machine Learning
NIPS 2023
Normalization Layers Are All That Sharpness-Aware Minimization Needs
NIPS 2023
SatBird: a Dataset for Bird Species Distribution Modeling using Remote Sensing and Citizen Science Data
NIPS 2023
Bugs in the Data: How ImageNet Misrepresents Biodiversity
AAAI 2023
Hard-Constrained Deep Learning for Climate Downscaling
JMLR 2023
FAENet: Frame Averaging Equivariant GNN for Materials Modeling
ICML 2023
Deep ReLU Networks Preserve Expected Length
ICLR 2022
Understanding the Evolution of Linear Regions in Deep Reinforcement Learning
NIPS 2022
Techniques for Symbol Grounding with SATNet
NIPS 2021
DC3: A learning method for optimization with hard constraints
ICLR 2021
Reverse-engineering deep ReLU networks
ICML 2020
Cross-Classification Clustering: An Efficient Multi-Object Tracking Technique for 3-D Instance Segmentation in Connectomics
CVPR 2019
Deep ReLU Networks Have Surprisingly Few Activation Patterns
NIPS 2019
Complexity of Linear Regions in Deep Networks
ICML 2019
Measuring and regularizing networks in function space
ICLR 2019
Experience Replay for Continual Learning
NIPS 2019
How to Start Training: The Effect of Initialization and Architecture
NIPS 2018
The power of deeper networks for expressing natural functions
ICLR 2018