A Forward-Backward Approach for Visualizing Information Flow in Deep Networks
We introduce a new, systematic framework for visualizing information flow in deep networks. Specifically, given any trained deep convolutional network model and a given test image, our method produces a compact support in the image domain that corresponds to a (high-resolution) feature that contributes to the given explanation. Our method is both computationally efficient as well as numerically robust. We present several preliminary numerical results that support the benefits of our framework over existing methods.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Backward Lens: Projecting Language Model Gradients into the Vocabulary Space
Understanding how Transformer-based Language Models (LMs) learn and recall information is a key goal of the deep learning community. Recent interpretability methods project weights and hidden states obtained from the for…
Language ModelingLanguage ModellingA Simplified Formulation for the Backward/Forward Sweep Power Flow Method
This paper describes a simplified formulation of the Backward/Forward (BW/FW) Sweep Power Flow applied to radial distribution systems with distributed generation under positive sequence modelling. Proposed formulation wa…
Re4: Learning to Re-contrast, Re-attend, Re-construct for Multi-interest Recommendation
Effectively representing users lie at the core of modern recommender systems. Since users' interests naturally exhibit multiple aspects, it is of increasing interest to develop multi-interest frameworks for recommendatio…
Contrastive LearningRecommendation SystemsFLUID: Flow-based Unified Inference for Dynamics
Bayesian filtering and smoothing for high-dimensional nonlinear dynamical systems are fundamental yet challenging problems in many areas of science and engineering. In this work, we propose FLUID, a flow-based unified am…
Forward Flow for Novel View Synthesis of Dynamic Scenes
This paper proposes a neural radiance field (NeRF) approach for novel view synthesis of dynamic scenes using forward warping. Existing methods often adopt a static NeRF to represent the canonical space, and render dynami…
NeRFNovel View Synthesis