Dimension Mixer: Group Mixing of Input Dimensions for Efficient Function Approximation
Fuente:
arXiv
Saved in:
| Main Authors: | Sapkota, Suman, Bhattarai, Binod |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Input Invex Neural Network
by: Sapkota, Suman, et al.
Published: (2021)
by: Sapkota, Suman, et al.
Published: (2021)
Metric as Transform: Exploring beyond Affine Transform for Interpretable Neural Network
by: Sapkota, Suman
Published: (2024)
by: Sapkota, Suman
Published: (2024)
General Loss Functions Lead to (Approximate) Interpolation in High Dimensions
by: Lai, Kuo-Wei, et al.
Published: (2023)
by: Lai, Kuo-Wei, et al.
Published: (2023)
On the Dimension-Free Approximation of Deep Neural Networks for Symmetric Korobov Functions
by: Lu, Yulong, et al.
Published: (2025)
by: Lu, Yulong, et al.
Published: (2025)
Beyond Token Eviction: Mixed-Dimension Budget Allocation for Efficient KV Cache Compression
by: Miao, Ruijie, et al.
Published: (2026)
by: Miao, Ruijie, et al.
Published: (2026)
MLP-SRGAN: A Single-Dimension Super Resolution GAN using MLP-Mixer
by: Mitha, Samir, et al.
Published: (2023)
by: Mitha, Samir, et al.
Published: (2023)
Variational LSTM with Augmented Inputs: Nonlinear Response History Metamodeling with Aleatoric and Epistemic Uncertainty
by: Sapkota, Manisha, et al.
Published: (2026)
by: Sapkota, Manisha, et al.
Published: (2026)
Dimension-Free Decision Calibration for Nonlinear Loss Functions
by: Tang, Jingwu, et al.
Published: (2025)
by: Tang, Jingwu, et al.
Published: (2025)
NERO: Explainable Out-of-Distribution Detection with Neuron-level Relevance
by: Chhetri, Anju, et al.
Published: (2025)
by: Chhetri, Anju, et al.
Published: (2025)
Active Label Refinement for Robust Training of Imbalanced Medical Image Classification Tasks in the Presence of High Label Noise
by: Khanal, Bidur, et al.
Published: (2024)
by: Khanal, Bidur, et al.
Published: (2024)
Anchoring Values in Temporal and Group Dimensions for Flow Matching Model Alignment
by: Shao, Yawen, et al.
Published: (2025)
by: Shao, Yawen, et al.
Published: (2025)
Hardware-Friendly Input Expansion for Accelerating Function Approximation
by: Lou, Hu, et al.
Published: (2026)
by: Lou, Hu, et al.
Published: (2026)
The No-Clash Teaching Dimension is Bounded by VC Dimension
by: Liu, Jiahua, et al.
Published: (2026)
by: Liu, Jiahua, et al.
Published: (2026)
Learning Functional Graphs with Nonlinear Sufficient Dimension Reduction
by: Kim, Kyongwon, et al.
Published: (2026)
by: Kim, Kyongwon, et al.
Published: (2026)
Low-Dimension-to-High-Dimension Generalization And Its Implications for Length Generalization
by: Chen, Yang, et al.
Published: (2024)
by: Chen, Yang, et al.
Published: (2024)
Rescaled Influence Functions: Accurate Data Attribution in High Dimension
by: Rubinstein, Ittai, et al.
Published: (2025)
by: Rubinstein, Ittai, et al.
Published: (2025)
The Rank-Reduced Kalman Filter: Approximate Dynamical-Low-Rank Filtering In High Dimensions
by: Schmidt, Jonathan, et al.
Published: (2023)
by: Schmidt, Jonathan, et al.
Published: (2023)
Symmetry Breaking in Neural Network Optimization: Insights from Input Dimension Expansion
by: Zhang, Jun-Jie, et al.
Published: (2024)
by: Zhang, Jun-Jie, et al.
Published: (2024)
Dimension-Free Convergence of Diffusion Models for Approximate Gaussian Mixtures
by: Li, Gen, et al.
Published: (2025)
by: Li, Gen, et al.
Published: (2025)
TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting
by: Wang, Shiyu, et al.
Published: (2024)
by: Wang, Shiyu, et al.
Published: (2024)
LLM-Mixer: Multiscale Mixing in LLMs for Time Series Forecasting
by: Kowsher, Md, et al.
Published: (2024)
by: Kowsher, Md, et al.
Published: (2024)
FFNet: MetaMixer-based Efficient Convolutional Mixer Design
by: Yun, Seokju, et al.
Published: (2024)
by: Yun, Seokju, et al.
Published: (2024)
How does self-supervised pretraining improve robustness against noisy labels across various medical image classification datasets?
by: Khanal, Bidur, et al.
Published: (2024)
by: Khanal, Bidur, et al.
Published: (2024)
Approximating Uniform Random Rotations by Two-Block Structured Hadamard Rotations in High Dimensions
by: Zilca, Tomer, et al.
Published: (2026)
by: Zilca, Tomer, et al.
Published: (2026)
DimGrow: Memory-Efficient Field-level Embedding Dimension Search
by: Huang, Yihong, et al.
Published: (2025)
by: Huang, Yihong, et al.
Published: (2025)
Two is better than one: A Collapse-free Multi-Reward RLIF Training Framework
by: Joarder, Shourov, et al.
Published: (2026)
by: Joarder, Shourov, et al.
Published: (2026)
The Dimension of Self-Directed Learning
by: Devulapalli, Pramith, et al.
Published: (2024)
by: Devulapalli, Pramith, et al.
Published: (2024)
Dimension Agnostic Neural Processes
by: Lee, Hyungi, et al.
Published: (2025)
by: Lee, Hyungi, et al.
Published: (2025)
Dimension Reduction for Symbolic Regression
by: Kahlmeyer, Paul, et al.
Published: (2025)
by: Kahlmeyer, Paul, et al.
Published: (2025)
Active Subspaces in Infinite Dimension
by: Kundu, Poorbita, et al.
Published: (2025)
by: Kundu, Poorbita, et al.
Published: (2025)
PatchMixer: A Patch-Mixing Architecture for Long-Term Time Series Forecasting
by: Gong, Zeying, et al.
Published: (2023)
by: Gong, Zeying, et al.
Published: (2023)
Multimodal Federated Learning With Missing Modalities through Feature Imputation Network
by: Poudel, Pranav, et al.
Published: (2025)
by: Poudel, Pranav, et al.
Published: (2025)
Approximation and Estimation Ability of Transformers for Sequence-to-Sequence Functions with Infinite Dimensional Input
by: Takakura, Shokichi, et al.
Published: (2023)
by: Takakura, Shokichi, et al.
Published: (2023)
U-Mixer: An Unet-Mixer Architecture with Stationarity Correction for Time Series Forecasting
by: Ma, Xiang, et al.
Published: (2024)
by: Ma, Xiang, et al.
Published: (2024)
SEMixer: Semantics Enhanced MLP-Mixer for Multiscale Mixing and Long-term Time Series Forecasting
by: Zhang, Xu, et al.
Published: (2026)
by: Zhang, Xu, et al.
Published: (2026)
MixMAS: A Framework for Sampling-Based Mixer Architecture Search for Multimodal Fusion and Learning
by: Chergui, Abdelmadjid, et al.
Published: (2024)
by: Chergui, Abdelmadjid, et al.
Published: (2024)
On the Intrinsic Dimensions of Data in Kernel Learning
by: Takhanov, Rustem
Published: (2026)
by: Takhanov, Rustem
Published: (2026)
Exploring the Dimensions of a Variational Neuron
by: Ruffenach, Yves
Published: (2026)
by: Ruffenach, Yves
Published: (2026)
Structural Dimension Reduction in Bayesian Networks
by: Heng, Pei, et al.
Published: (2026)
by: Heng, Pei, et al.
Published: (2026)
Dimension Reduction with Locally Adjusted Graphs
by: Wang, Yingfan, et al.
Published: (2024)
by: Wang, Yingfan, et al.
Published: (2024)
Similar Items
-
Input Invex Neural Network
by: Sapkota, Suman, et al.
Published: (2021) -
Metric as Transform: Exploring beyond Affine Transform for Interpretable Neural Network
by: Sapkota, Suman
Published: (2024) -
General Loss Functions Lead to (Approximate) Interpolation in High Dimensions
by: Lai, Kuo-Wei, et al.
Published: (2023) -
On the Dimension-Free Approximation of Deep Neural Networks for Symmetric Korobov Functions
by: Lu, Yulong, et al.
Published: (2025) -
Beyond Token Eviction: Mixed-Dimension Budget Allocation for Efficient KV Cache Compression
by: Miao, Ruijie, et al.
Published: (2026)