HyperAI초신경
홈
뉴스
최신 연구 논문
튜토리얼
데이터셋
백과사전
SOTA
LLM 모델
GPU 랭킹
컨퍼런스
전체 검색
소개
한국어
HyperAI초신경
Toggle sidebar
전체 사이트 검색...
⌘
K
홈
SOTA
Sequential Image Classification
Sequential Image Classification On Sequential 1
Sequential Image Classification On Sequential 1
평가 지표
Unpermuted Accuracy
평가 결과
이 벤치마크에서 각 모델의 성능 결과
Columns
모델 이름
Unpermuted Accuracy
Paper Title
Repository
S4
91.80%
Efficiently Modeling Long Sequences with Structured State Spaces
SMPConv
84.86%
SMPConv: Self-moving Point Representations for Continuous Convolution
Transformer (self-attention) (Trinh et al., 2018)
62.2%
Learning Longer-term Dependencies in RNNs with Auxiliary Losses
Sparse Combo Net
65.72
RNNs of RNNs: Recursive Construction of Stable Assemblies of Recurrent Neural Networks
MultiresConv
93.15%
Sequence Modeling with Multiresolution Convolutional Memory
LSSL
84.65%
Combining Recurrent, Convolutional, and Continuous-time Models with Linear State-Space Layers
CKCNN (1M)
63.74%
CKConv: Continuous Kernel Convolution For Sequential Data
LRU
89.0
Resurrecting Recurrent Neural Networks for Long Sequences
LipschitzRNN
64.2
Lipschitz Recurrent Neural Networks
FlexTCN-6
80.82%
FlexConv: Continuous Kernel Convolutions with Differentiable Kernel Sizes
Trellis Network
73.42%
Trellis Networks for Sequence Modeling
UR-GRU
74.4%
Improving the Gating Mechanism of Recurrent Neural Networks
CKCNN (100k)
62.25%
CKConv: Continuous Kernel Convolution For Sequential Data
0 of 13 row(s) selected.
Previous
Next