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Found 7 papers, 2 papers with code
On Exact Inversion of DPM-Solvers
Diffusion probabilistic models (DPMs) are a key component in modern generative models.
Neural Diffeomorphic Non-uniform B-spline Flows
In this work, we propose diffeomorphic non-uniform B-spline flows that are at least twice continuously differentiable while bi-Lipschitz continuous, enabling efficient parametrization while retaining analytic inverse transforms based on a sufficient condition for diffeomorphism.
On the Robustness of Normalizing Flows for Inverse Problems in Imaging
Most normalizing flows for inverse problems in imaging employ the conditional affine coupling layer that can generate diverse images quickly.
Efficient and Accurate Quantized Image Super-Resolution on Mobile NPUs, Mobile AI & AIM 2022 challenge: Report
While numerous solutions have been proposed for this problem in the past, they are usually not compatible with low-power mobile NPUs having many computational and memory constraints.
Efficient Single-Image Depth Estimation on Mobile Devices, Mobile AI & AIM 2022 Challenge: Report
Various depth estimation models are now widely used on many mobile and IoT devices for image segmentation, bokeh effect rendering, object tracking and many other mobile tasks.
DFX: A Low-latency Multi-FPGA Appliance for Accelerating Transformer-based Text Generation
DFX is also 8. 21x more cost-effective than the GPU appliance, suggesting that it is a promising solution for text generation workloads in cloud datacenters.
FIXAR: A Fixed-Point Deep Reinforcement Learning Platform with Quantization-Aware Training and Adaptive Parallelism
In this paper, we present a deep reinforcement learning platform named FIXAR which employs fixed-point data types and arithmetic units for the first time using a SW/HW co-design approach.
