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Found 9 papers, 4 papers with code
Condition-Aware Neural Network for Controlled Image Generation
In parallel to prior conditional control methods, CAN controls the image generation process by dynamically manipulating the weight of the neural network.
DistriFusion: Distributed Parallel Inference for High-Resolution Diffusion Models
To overcome this dilemma, we observe the high similarity between the input from adjacent diffusion steps and propose displaced patch parallelism, which takes advantage of the sequential nature of the diffusion process by reusing the pre-computed feature maps from the previous timestep to provide context for the current step.
Winning Prize Comes from Losing Tickets: Improve Invariant Learning by Exploring Variant Parameters for Out-of-Distribution Generalization
By fully exploring both variant and invariant parameters, our EVIL can effectively identify a robust subnetwork to improve OOD generalization.
AutoMLP: Automated MLP for Sequential Recommendations
Sequential recommender systems aim to predict users' next interested item given their historical interactions.
Efficient Spatially Sparse Inference for Conditional GANs and Diffusion Models
With about $1\%$-area edits, SIGE accelerates DDPM by $3. 0\times$ on NVIDIA RTX 3090 and $4. 6\times$ on Apple M1 Pro GPU, Stable Diffusion by $7. 2\times$ on 3090, and GauGAN by $5. 6\times$ on 3090 and $5. 2\times$ on M1 Pro GPU.
Mitigating the Performance Sacrifice in DP-Satisfied Federated Settings through Graph Contrastive Learning
Currently, graph learning models are indispensable tools to help researchers explore graph-structured data.
Lite Pose: Efficient Architecture Design for 2D Human Pose Estimation
Inspired by this finding, we design LitePose, an efficient single-branch architecture for pose estimation, and introduce two simple approaches to enhance the capacity of LitePose, including Fusion Deconv Head and Large Kernel Convs.
Ranked #5 on
Multi-Person Pose Estimation
on MS COCO
(Validation AP metric)
MLP4Rec: A Pure MLP Architecture for Sequential Recommendations
In addition, most existing works assume that such sequential dependencies exist solely in the item embeddings, but neglect their existence among the item features.
GAN Compression: Efficient Architectures for Interactive Conditional GANs
Directly applying existing compression methods yields poor performance due to the difficulty of GAN training and the differences in generator architectures.
