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Towards Flexible Inductive Bias via Progressive Reparameterization Scheduling
There are two de facto standard architectures in recent computer vision: Convolutional Neural Networks (CNNs) and Vision Transformers (ViTs). Strong...
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ViTAEv2: Vision Transformer Advanced by Exploring Inductive Bias for Image Recognition and Beyond
Vision transformers have shown great potential in various computer vision tasks owing to their strong capability to model long-range dependency using...
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A new deep learning architecture with inductive bias balance for transformer oil temperature forecasting
Ensuring the optimal performance of power transformers is a laborious task in which the insulation system plays a vital role in decreasing their...
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Introducing inductive bias on vision transformers through Gram matrix similarity based regularization
In recent years, the transformer achieved remarkable results in computer vision related tasks, matching, or even surpassing those of convolutional...
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Inductive Programming
Inductive programming is a branch of program synthesis that is based on inductive inference where a recursive, declarative program is constructed...
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Inductive Structure Consistent Hashing
Semantic-preserving hashing enhances multimedia retrieval by transferring knowledge from original data to hash codes, preserving both visual and...
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Equivariance and Invariance Inductive Bias for Learning from Insufficient Data
We are interested in learning robust models from insufficient data, without the need for any externally pre-trained checkpoints. First, compared to...
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Generalizable inductive relation prediction with causal subgraph
Inductive relation prediction is an important learning task for knowledge graph reasoning that aims to infer new facts from existing ones. Previous...
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An Iterative Graph Learning Convolution Network for Key Information Extraction Based on the Document Inductive Bias
Recently, there has been growing interest in automating the extraction of key information from document images. Previous methods mainly focus on...
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Voltage controlled oscillator with active inductive and capacitive tuning
This work reports a new design of three stage ring voltage controlled oscillator (VCO) with MOS varactor and active inductor tuning concept. A...
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Graph Networks as Inductive Bias for Genetic Programming: Symbolic Models for Particle-Laden Flows
High-resolution simulations of particle-laden flows are computationally limited to a scale of thousands of particles due to the complex interactions...
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Media Bias Analysis
This chapter provides the first interdisciplinary literature review on media bias analysis, thereby contrasting manual and automated analysis...
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Robust Domain Adaptation: Representations, Weights and Inductive Bias
Unsupervised Domain Adaptation (UDA) has attracted a lot of attention in the last ten years. The emergence of Domain Invariant Representations (IR)...
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Enabling inductive knowledge graph completion via structure-aware attention network
AbstractKnowledge graph completion (KGC) aims at complementing missing entities and relations in a knowledge graph (KG). Popular KGC approaches based...
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Automated Analysis of Diabetic Retinopathy Using Vessel Segmentation Maps as Inductive Bias
Recent studies suggest that early stages of diabetic retinopathy (DR) can be diagnosed by monitoring vascular changes in the deep vascular complex....
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OccamNets: Mitigating Dataset Bias by Favoring Simpler Hypotheses
Dataset bias and spurious correlations can significantly impair generalization in deep neural networks. Many prior efforts have addressed this...
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Inductive Multi-View Semi-supervised Learning with a Consensus Graph
Graphs have a crucial impact on the performance of any graph-based semi-supervised learning method, so their construction should be carefully...
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A 70%-power transmission efficiency, 3.39 Mbps power and data telemetry over a single 13.56 MHz inductive link for biomedical implants
The application of wireless power and data telemetry to implantable medical devices (IMDs) has grown dramatically in recent decades. Achieving a high...
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Imposing Rules in Process Discovery: An Inductive Mining Approach
Process discovery aims to discover descriptive process models from event logs. These discovered process models depict the actual execution of a...
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Artificial intelligence bias in medical system designs: a systematic review
Inherent bias in the artificial intelligence (AI)-model brings inaccuracies and variabilities during clinical deployment of the model. It is...
