68 citations · 154 across the 10 of their papers we have counts for
10 papers
Rethinking Zero-shot Video Classification: End-to-end Training for Realistic Applications
Biagio Brattoli, Joseph Tighe, Fedor Zhdanov +2
Trained on large datasets, deep learning (DL) can accurately classify videos into hundreds of diverse classes. However, video data is expensive to annotate. Zero-shot learning (ZSL…
Causal Regularization
Dominik Janzing
I argue that regularizing terms in standard regression methods not only help against overfitting finite data, but sometimes also yield better causal models in the infinite sample r…
Fast Conditional Independence Test for Vector Variables with Large Sample Sizes
Krzysztof Chalupka, Pietro Perona, Frederick Eberhardt
We present and evaluate the Fast (conditional) Independence Test (FIT) -- a nonparametric conditional independence test. The test is based on the idea that when $P(X \mid Y, Z) = P…
Causal Regularization
Mohammad Taha Bahadori, Krzysztof Chalupka, Edward Choi +3
In application domains such as healthcare, we want accurate predictive models that are also causally interpretable. In pursuit of such models, we propose a causal regularizer to st…
Estimating Causal Direction and Confounding of Two Discrete Variables
Krzysztof Chalupka, Frederick Eberhardt, Pietro Perona
We propose a method to classify the causal relationship between two discrete variables given only the joint distribution of the variables, acknowledging that the method is subject…
Unsupervised Discovery of El Nino Using Causal Feature Learning on Microlevel Climate Data
Krzysztof Chalupka, Tobias Bischoff, Pietro Perona +1
We show that the climate phenomena of El Nino and La Nina arise naturally as states of macro-variables when our recent causal feature learning framework (Chalupka 2015, Chalupka 20…
Multi-Level Cause-Effect Systems
Krzysztof Chalupka, Pietro Perona, Frederick Eberhardt
We present a domain-general account of causation that applies to settings in which macro-level causal relations between two systems are of interest, but the relevant causal feature…
Generalized Regressive Motion: a Visual Cue to Collision
Krzysztof Chalupka, Michael Dickinson, Pietro Perona
Brains and sensory systems evolved to guide motion. Central to this task is controlling the approach to stationary obstacles and detecting moving organisms. Looming has been propos…
Visual Causal Feature Learning
Krzysztof Chalupka, Pietro Perona, Frederick Eberhardt
We provide a rigorous definition of the visual cause of a behavior that is broadly applicable to the visually driven behavior in humans, animals, neurons, robots and other perceivi…
A Framework for Evaluating Approximation Methods for Gaussian Process Regression
Krzysztof Chalupka, Christopher K. I. Williams, Iain Murray
Gaussian process (GP) predictors are an important component of many Bayesian approaches to machine learning. However, even a straightforward implementation of Gaussian process regr…