convolution
RangePerception: Taming LiDAR Range View for Efficient and Accurate 3D Object Detection Y eqi Bai 1 Ben Fei
LiDAR-based 3D detection methods currently use bird's-eye view (BEV) or range
- North America > Canada > Alberta > Census Division No. 6 > Calgary Metropolitan Region > Calgary (0.14)
- North America > United States (0.04)
- Europe > Italy > Calabria > Catanzaro Province > Catanzaro (0.04)
- Asia > Japan > Honshū > Tōhoku > Fukushima Prefecture > Fukushima (0.04)
- North America > United States > California > Santa Clara County > Palo Alto (0.04)
- North America > United States > Texas (0.04)
- Europe > Italy > Calabria > Catanzaro Province > Catanzaro (0.04)
State-space Models with Layer-wise Nonlinearity are Universal Approximators with Exponential Decaying Memory
State-space models have gained popularity in sequence modelling due to their simple and efficient network structures. However, the absence of nonlinear activation along the temporal direction limits the model's capacity.
- Asia > Singapore (0.04)
- North America > United States > Rhode Island > Providence County > Providence (0.04)
- Europe > United Kingdom > England > Cambridgeshire > Cambridge (0.04)
- Asia > China (0.04)
Supplemental Material
Figure 1: Overview of the Transformer block used in the PromptIR framework. As mentioned in section 3.1.2 Bias-free convolutions are utilized within this submodule. After MDT A Module the features are processed through the GDFN module. Our method effectively removes haze to produce visually better images.
FourierGNN: Rethinking Multivariate Time Series Forecasting from a Pure Graph Perspective Kun Yi
Multivariate time series (MTS) forecasting has shown great importance in numerous industries.
- South America > Chile > Santiago Metropolitan Region > Santiago Province > Santiago (0.04)
- North America > United States > California > San Francisco County > San Francisco (0.04)
- North America > United States > California > Los Angeles County (0.04)
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- Energy (1.00)
- Information Technology (0.67)
Equivariant Neural Operator Learning with Graphon Convolution
It is common that these data themselves have inherently complicated 3D geometric structures.
- Oceania > Australia > New South Wales > Sydney (0.04)
- North America > United States > Illinois > Champaign County > Urbana (0.04)
- Europe > Germany > Bavaria > Upper Bavaria > Munich (0.04)
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- Materials > Chemicals > Commodity Chemicals > Petrochemicals (0.68)
- Health & Medicine (0.68)
Equivariant Neural Operator Learning with Graphon Convolution
It is common that these data themselves have inherently complicated 3D geometric structures.
- Oceania > Australia > New South Wales > Sydney (0.04)
- North America > United States > Illinois > Champaign County > Urbana (0.04)
- Europe > Germany > Bavaria > Upper Bavaria > Munich (0.04)
- (9 more...)
- Materials > Chemicals > Commodity Chemicals > Petrochemicals (0.68)
- Health & Medicine (0.68)
- Research Report > Promising Solution (0.47)
- Research Report > New Finding (0.46)