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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 3476–3500 of 4891 papers

TitleStatusHype
Joint Semantic Transfer Network for IoT Intrusion Detection—0
Adaptive physics-informed neural operator for coarse-grained non-equilibrium flows—0
Analyzing Deep Learning Representations of Point Clouds for Real-Time In-Vehicle LiDAR Perception—0
Bridging Distributional and Risk-sensitive Reinforcement Learning with Provable Regret Bounds—0
SeismicNet: Physics-informed neural networks for seismic wave modeling in semi-infinite domain—0
The mass-conversion method: a hybrid technique for simulating well-mixed chemical reaction networks—0
Joint Speech Translation and Named Entity Recognition—0
Frequency of Interest-based Noise Attenuation Method to Improve Anomaly Detection Performance—0
gSuite: A Flexible and Framework Independent Benchmark Suite for Graph Neural Network Inference on GPUs—0
Graph sampling for node embedding—0
Phenomenological Model of Superconducting Optoelectronic Loop Neurons—0
RibSeg v2: A Large-scale Benchmark for Rib Labeling and Anatomical Centerline ExtractionCode0
Accelerate Three-Dimensional Generative Adversarial Networks Using Fast Algorithm—0
A Novel Membership Inference Attack against Dynamic Neural Networks by Utilizing Policy Networks Information—0
Dynamics-aware Adversarial Attack of Adaptive Neural NetworksCode0
Latent Temporal Flows for Multivariate Analysis of Wearables Data—0
An Efficient FPGA Accelerator for Point Cloud—0
Graph Neural Network Surrogate for Seismic Reliability Analysis of Highway Bridge Systems—0
Deep Koopman Learning of Nonlinear Time-Varying Systems—0
Model Cascading: Towards Jointly Improving Efficiency and Accuracy of NLP Systems—0
FaDIn: Fast Discretized Inference for Hawkes Processes with General Parametric Kernels—0
Design Amortization for Bayesian Optimal Experimental Design—0
Efficient Diffusion Models for Vision: A Survey—0
Fast Saturating Gate for Learning Long Time Scales with Recurrent Neural Networks—0
Deep Learning-based Facial Appearance Simulation Driven by Surgically Planned Craniomaxillofacial Bony Movement—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified