33 citations · 87 across the 7 of their papers we have counts for
7 papers
Universality of Gaussian-Mixture Reverse Kernels in Conditional Diffusion
Nafiz Ishtiaque, Syed Arefinul Haque, Kazi Ashraful Alam +1
We prove that conditional diffusion models whose reverse kernels are finite Gaussian mixtures with ReLU-network logits can approximate suitably regular target distributions arbitra…
CAM-Seg: A Continuous-valued Embedding Approach for Semantic Image Generation
Masud Ahmed, Zahid Hasan, Syed Arefinul Haque +4
Traditional transformer-based semantic segmentation relies on quantized embeddings. However, our analysis reveals that autoencoder accuracy on segmentation mask using quantized emb…
Persistence Homology of TEDtalk: Do Sentence Embeddings Have a Topological Shape?
Shouman Das, Syed A. Haque, Md. Iftekhar Tanveer
\emph{Topological data analysis} (TDA) has recently emerged as a new technique to extract meaningful discriminitve features from high dimensional data. In this paper, we investigat…
netrd: A library for network reconstruction and graph distances
Stefan McCabe, Leo Torres, Timothy LaRock +4
Over the last two decades, alongside the increased availability of large network datasets, we have witnessed the rapid rise of network science. For many systems, however, the data…
Classical Music Clustering Based on Acoustic Features
Xindi Wang, Syed Arefinul Haque
In this paper we cluster 330 classical music pieces collected from MusicNet database based on their musical note sequence. We use shingling and chord trajectory matrices to create…
Degree Distribution, Rank-size Distribution, and Leadership Persistence in Mediation-Driven Attachment Networks
Md. Kamrul Hassan, Liana Islam, Syed Arefinul Haque
We investigate the growth of a class of networks in which a new node first picks a mediator at random and connects with randomly chosen neighbors of the mediator at each time s…
Growing Scale-free Networks by a Mediation-Driven Attachment Rule
Kamrul Hassan, Liana Islam
We propose a model that generates a new class of networks exhibiting power-law degree distribution with a spectrum of exponents depending on the number of links () with which in…