431 citations · 579 across the 9 of their papers we have counts for
9 papers
Learning Causal State Representations of Partially Observable Environments
Amy Zhang, Zachary C. Lipton, Luis Pineda +5
Intelligent agents can cope with sensory-rich environments by learning task-agnostic state abstractions. In this paper, we propose an algorithm to approximate causal states, which…
Born Again Neural Networks
Tommaso Furlanello, Zachary C. Lipton, Michael Tschannen +2
Knowledge Distillation (KD) consists of transferring “knowledge†from one machine learning model (the teacher) to another (the student). Commonly, the teacher is a high-capacit…
Question Type Guided Attention in Visual Question Answering
Yang Shi, Tommaso Furlanello, Sheng Zha +1
Visual Question Answering (VQA) requires integration of feature maps with drastically different structures and focus of the correct regions. Image descriptors have structures at mu…
Tensor Regression Networks
Jean Kossaifi, Zachary C. Lipton, Arinbjorn Kolbeinsson +3
Convolutional neural networks typically consist of many convolutional layers followed by one or more fully connected layers. While convolutional layers map between high-order activ…
Compact Tensor Pooling for Visual Question Answering
Yang Shi, Tommaso Furlanello, Anima Anandkumar
Performing high level cognitive tasks requires the integration of feature maps with drastically different structure. In Visual Question Answering (VQA) image descriptors have spati…
Tensor Contraction Layers for Parsimonious Deep Nets
Jean Kossaifi, Aran Khanna, Zachary C. Lipton +2
Tensors offer a natural representation for many kinds of data frequently encountered in machine learning. Images, for example, are naturally represented as third order tensors, whe…
Active Long Term Memory Networks
Tommaso Furlanello, Jiaping Zhao, Andrew M. Saxe +2
Continual Learning in artificial neural networks suffers from interference and forgetting when different tasks are learned sequentially. This paper introduces the Active Long Term…
Entropy Dynamics of Community Alignment in the Italian Parliament Time-Dependent Network
Gabriele Lami, Marco Cristoforetti, Giuseppe Jurman +2
Complex institutions are typically characterized by meso-scale structures which are fundamental for the successful coordination of multiple agents. Here we introduce a framework to…
Sparse Predictive Structure of Deconvolved Functional Brain Networks
Tommaso Furlanello, Marco Cristoforetti, Cesare Furlanello +1
The functional and structural representation of the brain as a complex network is marked by the fact that the comparison of noisy and intrinsically correlated high-dimensional stru…