activity
20162023
most citedTechnical Report on the CleverHans v2.1.0 Adversarial Examples Library

401 citations · 807 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CV2023

Compositional diversity in visual concept learning

Yanli Zhou, Reuben Feinman, Brenden M. Lake

Humans leverage compositionality to efficiently learn new concepts, understanding how familiar parts can combine together to form novel objects. In contrast, popular computer visio…

cs.AI2020★ 5 cited

Learning Task-General Representations with Generative Neuro-Symbolic Modeling

Reuben Feinman, Brenden M. Lake

People can learn rich, general-purpose conceptual representations from only raw perceptual inputs. Current machine learning approaches fall well short of these human standards, alt…

cs.LG2020★ 5 cited

Generating new concepts with hybrid neuro-symbolic models

Reuben Feinman, Brenden M. Lake

Human conceptual knowledge supports the ability to generate novel yet highly structured concepts, and the form of this conceptual knowledge is of great interest to cognitive scient…

cs.LG2019

A Linear Systems Theory of Normalizing Flows

Reuben Feinman, Nikhil Parthasarathy

Normalizing Flows are a promising new class of algorithms for unsupervised learning based on maximum likelihood optimization with change of variables. They offer to learn a factori…

cs.CV2019★ 3 cited

Learning a smooth kernel regularizer for convolutional neural networks

Reuben Feinman, Brenden M. Lake

Modern deep neural networks require a tremendous amount of data to train, often needing hundreds or thousands of labeled examples to learn an effective representation. For these ne…

cs.CL2018★ 27 cited

Learning Inductive Biases with Simple Neural Networks

Reuben Feinman, Brenden M. Lake

People use rich prior knowledge about the world in order to efficiently learn new concepts. These priors - also known as "inductive biases" - pertain to the space of internal model…

stat.ML2017★ 366 cited

Detecting Adversarial Samples from Artifacts

Reuben Feinman, Ryan R. Curtin, Saurabh Shintre +1

Deep neural networks (DNNs) are powerful nonlinear architectures that are known to be robust to random perturbations of the input. However, these models are vulnerable to adversari…

cs.LG2016★ 401 cited

Technical Report on the CleverHans v2.1.0 Adversarial Examples Library

Nicolas Papernot, Fartash Faghri, Nicholas Carlini +23

CleverHans is a software library that provides standardized reference implementations of adversarial example construction techniques and adversarial training. The library may be us…