SOTAVerified

Computational Efficiency

Methods and optimizations to reduce the computational resources (e.g., time, memory, or power) needed for training and inference in models. This involves techniques that streamline processing, optimize algorithms, or leverage hardware to enhance performance without compromising accuracy.

Papers

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Showing 2481–2490 of 4891 papers

TitleStatusHype
Time-Aware Knowledge Representations of Dynamic Objects with Multidimensional Persistence—0
PlaceFormer: Transformer-based Visual Place Recognition using Multi-Scale Patch Selection and Fusion—0
An Efficient Implicit Neural Representation Image Codec Based on Mixed Autoregressive Model for Low-Complexity Decoding—0
CIS-UNet: Multi-Class Segmentation of the Aorta in Computed Tomography Angiography via Context-Aware Shifted Window Self-AttentionCode1
Falcon: Fair Active Learning using Multi-armed BanditsCode0
DITTO: Diffusion Inference-Time T-Optimization for Music Generation—0
A Review of Physics-Informed Machine Learning Methods with Applications to Condition Monitoring and Anomaly Detection—0
MOSformer: Momentum encoder-based inter-slice fusion transformer for medical image segmentation—0
OnDev-LCT: On-Device Lightweight Convolutional Transformers towards federated learning—0
TIM: An Efficient Temporal Interaction Module for Spiking Transformer—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified