Papers
Image Synthesis with a Convolutional Capsule Generative Adversarial Network
Cher Bass, Tianhong Dai, Benjamin Billot et al.
On the Spatial and Temporal Influence for the Reconstruction of Magnetic Resonance Fingerprinting
Fabian Balsiger, Olivier Scheidegger, Pierre G. Carlier et al.
Exploring local rotation invariance in 3D CNNs with steerable filters
Vincent Andrearczyk, Julien Fageot, Valentin Oreiller et al.
AnatomyGen: Deep Anatomy Generation From Dense Representation With Applications in Mandible Synthesis
Amir H. Abdi, Heather Borgard, Purang Abolmaesumi et al.
Why do deep convolutional networks generalize so poorly to small image transformations?
Aharon Azulay, Yair Weiss
Log-concave sampling: Metropolis-Hastings algorithms are fast
Raaz Dwivedi, Yuansi Chen, Martin J. Wainwright et al.
Model Selection in Bayesian Neural Networks via Horseshoe Priors
Soumya Ghosh, Jiayu Yao, Finale Doshi-Velez
Neural Empirical Bayes
Saeed Saremi, Aapo Hyvärinen
DPPy: DPP Sampling with Python
Guillaume Gautier, Guillermo Polito, Rémi Bardenet et al.
Differentiable reservoir computing
Lyudmila Grigoryeva, Juan-Pablo Ortega
Morpho-MNIST: Quantitative Assessment and Diagnostics for Representation Learning
Daniel C. Castro, Jeremy Tan, Bernhard Kainz et al.
All Models are Wrong, but Many are Useful: Learning a Variable's Importance by Studying an Entire Class of Prediction Models Simultaneously
Aaron Fisher, Cynthia Rudin, Francesca Dominici
New Convergence Aspects of Stochastic Gradient Algorithms
Lam M. Nguyen, Phuong Ha Nguyen, Peter Richtárik et al.
DataWig: Missing Value Imputation for Tables
Felix Biessmann, Tammo Rukat, Phillipp Schmidt et al.
Learning Overcomplete, Low Coherence Dictionaries with Linear Inference
Jesse A. Livezey, Alejandro F. Bujan, Friedrich T. Sommer
Fast Automatic Smoothing for Generalized Additive Models
Yousra El-Bachir, Anthony C. Davison
Optimization with Non-Differentiable Constraints with Applications to Fairness, Recall, Churn, and Other Goals
Andrew Cotter, Heinrich Jiang, Maya Gupta et al.
Shared Subspace Models for Multi-Group Covariance Estimation
Alexander M. Franks, Peter Hoff
DBSCAN: Optimal Rates For Density-Based Cluster Estimation
Daren Wang, Xinyang Lu, Alessandro Rinaldo
Embarrassingly Parallel Inference for Gaussian Processes
Michael Minyi Zhang, Sinead A. Williamson
Determinantal Point Processes for Coresets
Nicolas Tremblay, Simon Barthelmé, Pierre-Olivier Amblard
Stochastic Canonical Correlation Analysis
Chao Gao, Dan Garber, Nathan Srebro et al.
Unsupervised Evaluation and Weighted Aggregation of Ranked Classification Predictions
Mehmet Eren Ahsen, Robert M Vogel, Gustavo A Stolovitzky
On the Convergence of Gaussian Belief Propagation with Nodes of Arbitrary Size
Francois Kamper, Sarel J. Steel, Johan A. du Preez
The Reduced PC-Algorithm: Improved Causal Structure Learning in Large Random Networks
Arjun Sondhi, Ali Shojaie