2024
PhAST: Physics-Aware, Scalable, and Task-Specific GNNs for Accelerated Catalyst Design.
J. Mach. Learn. Res., 2024
Alberta Wells Dataset: Pinpointing Oil and Gas Wells from Satellite Imagery.
CoRR, 2024
Causal Representation Learning in Temporal Data via Single-Parent Decoding.
CoRR, 2024
Tree semantic segmentation from aerial image time series.
CoRR, 2024
Evaluating the transferability potential of deep learning models for climate downscaling.
CoRR, 2024
Improving Molecular Modeling with Geometric GNNs: an Empirical Study.
CoRR, 2024
A machine learning pipeline for automated insect monitoring.
CoRR, 2024
Climate Variable Downscaling with Conditional Normalizing Flows.
CoRR, 2024
Predicting Species Occurrence Patterns from Partial Observations.
CoRR, 2024
Application-Driven Innovation in Machine Learning.
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CoRR, 2024
Dataset Difficulty and the Role of Inductive Bias.
CoRR, 2024
Simultaneous Linear Connectivity of Neural Networks Modulo Permutation.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2024
Position: Application-Driven Innovation in Machine Learning.
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Proceedings of the Forty-first International Conference on Machine Learning, 2024
Stealing part of a production language model.
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Proceedings of the Forty-first International Conference on Machine Learning, 2024
Insect Identification in the Wild: The AMI Dataset.
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Proceedings of the Computer Vision - ECCV 2024, 2024
2023
Hard-Constrained Deep Learning for Climate Downscaling.
J. Mach. Learn. Res., 2023
Tackling Climate Change with Machine Learning.
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ACM Comput. Surv., 2023
FoMo-Bench: a multi-modal, multi-scale and multi-task Forest Monitoring Benchmark for remote sensing foundation models.
CoRR, 2023
Towards Causal Representations of Climate Model Data.
CoRR, 2023
SatBird: Bird Species Distribution Modeling with Remote Sensing and Citizen Science Data.
CoRR, 2023
OpenForest: A data catalogue for machine learning in forest monitoring.
CoRR, 2023
On the importance of catalyst-adsorbate 3D interactions for relaxed energy predictions.
CoRR, 2023
Multi-variable Hard Physical Constraints for Climate Model Downscaling.
CoRR, 2023
Fourier Neural Operators for Arbitrary Resolution Climate Data Downscaling.
CoRR, 2023
Bird Distribution Modelling using Remote Sensing and Citizen Science data.
CoRR, 2023
Lightweight, Pre-trained Transformers for Remote Sensing Timeseries.
CoRR, 2023
Deep Networks as Paths on the Manifold of Neural Representations.
Proceedings of the Topological, 2023
SatBird: a Dataset for Bird Species Distribution Modeling using Remote Sensing and Citizen Science Data.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Normalization Layers Are All That Sharpness-Aware Minimization Needs.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
ClimateSet: A Large-Scale Climate Model Dataset for Machine Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Maximal Initial Learning Rates in Deep ReLU Networks.
Proceedings of the International Conference on Machine Learning, 2023
Hidden Symmetries of ReLU Networks.
Proceedings of the International Conference on Machine Learning, 2023
FAENet: Frame Averaging Equivariant GNN for Materials Modeling.
Proceedings of the International Conference on Machine Learning, 2023
Bugs in the Data: How ImageNet Misrepresents Biodiversity.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
2022
Clustering units in neural networks: upstream vs downstream information.
Trans. Mach. Learn. Res., 2022
Generating physically-consistent high-resolution climate data with hard-constrained neural networks.
CoRR, 2022
Neural Networks as Paths through the Space of Representations.
CoRR, 2022
On Neural Architecture Inductive Biases for Relational Tasks.
CoRR, 2022
TIML: Task-Informed Meta-Learning for Agriculture.
CoRR, 2022
Understanding the Evolution of Linear Regions in Deep Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Deep ReLU Networks Preserve Expected Length.
Proceedings of the Tenth International Conference on Learning Representations, 2022
2021
Hidden Hypergraphs, Error-Correcting Codes, and Critical Learning in Hopfield Networks.
Entropy, 2021
Geo-Spatiotemporal Features and Shape-Based Prior Knowledge for Fine-grained Imbalanced Data Classification.
CoRR, 2021
Techniques for Symbol Grounding with SATNet.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
ClimART: A Benchmark Dataset for Emulating Atmospheric Radiative Transfer in Weather and Climate Models.
Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021
DC3: A learning method for optimization with hard constraints.
Proceedings of the 9th International Conference on Learning Representations, 2021
2020
Reverse-engineering deep ReLU networks.
Proceedings of the 37th International Conference on Machine Learning, 2020
2019
Identifying Weights and Architectures of Unknown ReLU Networks.
CoRR, 2019
Experience Replay for Continual Learning.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Deep ReLU Networks Have Surprisingly Few Activation Patterns.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Randomized Experimental Design via Geographic Clustering.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019
Complexity of Linear Regions in Deep Networks.
Proceedings of the 36th International Conference on Machine Learning, 2019
Measuring and regularizing networks in function space.
Proceedings of the 7th International Conference on Learning Representations, 2019
Cross-Classification Clustering: An Efficient Multi-Object Tracking Technique for 3-D Instance Segmentation in Connectomics.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019
2018
Cross-Classification Clustering: An Efficient Multi-Object Tracking Technique for 3-D Instance Segmentation in Connectomics.
CoRR, 2018
How to Start Training: The Effect of Initialization and Architecture.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
The power of deeper networks for expressing natural functions.
Proceedings of the 6th International Conference on Learning Representations, 2018
2017
On the classification of Stanley sequences.
Eur. J. Comb., 2017
Quantitative (p, q) theorems in combinatorial geometry.
Discret. Math., 2017
Quantitative Tverberg Theorems Over Lattices and Other Discrete Sets.
Discret. Comput. Geom., 2017
Quantitative Combinatorial Geometry for Continuous Parameters.
Discret. Comput. Geom., 2017
Deep Learning is Robust to Massive Label Noise.
CoRR, 2017
Morphological Error Detection in 3D Segmentations.
CoRR, 2017
Markov Transitions between Attractor States in a Recurrent Neural Network.
Proceedings of the 2017 AAAI Spring Symposia, 2017
2016
Novel structures in Stanley sequences.
Discret. Math., 2016
Algorithmic aspects of Tverberg's Theorem.
CoRR, 2016
GeoCUTS: Geographic Clustering Using Travel Statistics.
CoRR, 2016
A Multi-Pass Approach to Large-Scale Connectomics.
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CoRR, 2016
2015
On the growth of Stanley sequences.
Discret. Math., 2015
On the robust hardness of Gröbner basis computation.
CoRR, 2015
Acyclic Subgraphs of Planar Digraphs.
Electron. J. Comb., 2015
Graph-Coloring Ideals: Nullstellensatz Certificates, Gröbner Bases for Chordal Graphs, and Hardness of Gröbner Bases.
Proceedings of the 2015 ACM on International Symposium on Symbolic and Algebraic Computation, 2015
2014
Gröbner Bases and Nullstellensätze for Graph-Coloring Ideals.
CoRR, 2014
2013
The on-line degree Ramsey number of cycles.
Discret. Math., 2013
2011
Trees with an On-Line Degree Ramsey Number of Four.
Electron. J. Comb., 2011