3 papers
cs.LG2025
A Selective Quantization Tuner for ONNX Models
Nikolaos Louloudakis, Ajitha Rajan
Quantization reduces the precision of deep neural networks to lower model size and computational demands, but often at the expense of accuracy. Fully quantized models can suffer si…
cs.LG2025
DiTOX: Fault Detection and Localization in the ONNX Optimizer
Nikolaos Louloudakis, Ajitha Rajan
The ONNX Optimizer, part of the official ONNX repository and widely adopted for graph-level model optimizations, is used by default to optimize ONNX models. Despite its popularity,…
cs.CV2025
Metric-Guided Synthesis of Class Activation Mapping
Alejandro Luque-Cerpa, Elizabeth Polgreen, Ajitha Rajan +1
Class activation mapping (CAM) is a widely adopted class of saliency methods used to explain the behavior of convolutional neural networks (CNNs). These methods generate heatmaps t…