7 papers
Diverse Subset Selection via Norm-Based Sampling and Orthogonality
Noga Bar, Raja Giryes
Large annotated datasets are crucial for the success of deep neural networks, but labeling data can be prohibitively expensive in domains such as medical imaging. This work tackles…
DIP-GS: Deep Image Prior For Gaussian Splatting Sparse View Recovery
Rajaei Khatib, Raja Giryes
3D Gaussian Splatting (3DGS) is a leading 3D scene reconstruction method, obtaining high-quality reconstruction with real-time rendering runtime performance. The main idea behind 3…
Revisiting Glorot Initialization for Long-Range Linear Recurrences
Noga Bar, Mariia Seleznova, Yotam Alexander +2
Proper initialization is critical for Recurrent Neural Networks (RNNs), particularly in long-range reasoning tasks, where repeated application of the same weight matrix can cause v…
ZOQO: Zero-Order Quantized Optimization
Noga Bar, Raja Giryes
The increasing computational and memory demands in deep learning present significant challenges, especially in resource-constrained environments. We introduce a zero-order quantize…
TriNeRFLet: A Wavelet Based Triplane NeRF Representation
Rajaei Khatib, Raja Giryes
In recent years, the neural radiance field (NeRF) model has gained popularity due to its ability to recover complex 3D scenes. Following its success, many approaches proposed diffe…
How do Transformers perform In-Context Autoregressive Learning?
Michael E. Sander, Raja Giryes, Taiji Suzuki +2
Transformers have achieved state-of-the-art performance in language modeling tasks. However, the reasons behind their tremendous success are still unclear. In this paper, towards a…