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no code implementations • 1 Feb 2023 • Saurabh Sharma, Yongqin Xian, Ning Yu, Ambuj Singh

On the other hand, Prototype classifiers do not suffer from this shortcoming and can deliver promising results simply using Nearest-Class-Mean (NCM), a special case where prototypes are empirical centroids.

Ranked #5 on Long-tail Learning on CIFAR-100-LT (ρ=10)

1 code implementation • 21 Oct 2022 • Mert Kosan, Zexi Huang, Sourav Medya, Sayan Ranu, Ambuj Singh

One way to address this is counterfactual reasoning where the objective is to change the GNN prediction by minimal changes in the input graph.

1 code implementation • 23 May 2022 • Sikun Lin, Shuyun Tang, Scott Grafton, Ambuj Singh

Finding an appropriate representation of dynamic activities in the brain is crucial for many downstream applications.

1 code implementation • 15 Mar 2022 • Wei Ye, Jiayi Yang, Sourav Medya, Ambuj Singh

Graph neural networks (GNNs) often assume strong homophily in graphs, seldom considering heterophily which means connected nodes tend to have different class labels and dissimilar features.

1 code implementation • 24 Jan 2022 • Wei Ye, Zexi Huang, Yunqi Hong, Ambuj Singh

To solve these two issues, we propose a new graph neural network called GND-Nets (for Graph Neural Diffusion Networks) that exploits the local and global neighborhood information of a vertex in a single layer.

1 code implementation • 24 Oct 2021 • Zexi Huang, Arlei Silva, Ambuj Singh

Graph embedding based on random-walks supports effective solutions for many graph-related downstream tasks.

1 code implementation • 23 Oct 2021 • Mert Kosan, Arlei Silva, Sourav Medya, Brian Uzzi, Ambuj Singh

In this paper, we propose DyGED, a simple yet novel deep learning model for event detection on dynamic graphs.

1 code implementation • 17 Oct 2021 • Zexi Huang, Arlei Silva, Ambuj Singh

From the 2016 U. S. presidential election to the 2021 Capitol riots to the spread of misinformation related to COVID-19, many have blamed social media for today's deeply divided society.

no code implementations • ICLR 2021 • Arlei Lopes da Silva, Furkan Kocayusufoglu, Saber Jafarpour, Francesco Bullo, Ananthram Swami, Ambuj Singh

The flow estimation problem consists of predicting missing edge flows in a network (e. g., traffic, power and water) based on partial observations.

1 code implementation • 5 Apr 2020 • Wei Ye, Omid Askarisichani, Alex Jones, Ambuj Singh

The learned deep representation for a graph is a dense and low-dimensional vector that captures complex high-order interactions in a vertex neighborhood.

1 code implementation • 24 Mar 2020 • Wei Ye, Dominik Mautz, Christian Boehm, Ambuj Singh, Claudia Plant

In contrast to global clustering, local clustering aims to find only one cluster that is concentrating on the given seed vertex (and also on the designated attributes for attributed graphs).

1 code implementation • 23 Feb 2020 • Wei Ye, Zhen Wang, Rachel Redberg, Ambuj Singh

At the heart of Tree++ is a graph kernel called the path-pattern graph kernel.

2 code implementations • NeurIPS 2020 • Sahil Manchanda, Akash Mittal, Anuj Dhawan, Sourav Medya, Sayan Ranu, Ambuj Singh

Additionally, a case-study on the practical combinatorial problem of Influence Maximization (IM) shows GCOMB is 150 times faster than the specialized IM algorithm IMM with similar quality.

no code implementations • 30 Sep 2016 • Xuan-Hong Dang, Arlei Silva, Ambuj Singh, Ananthram Swami, Prithwish Basu

Detecting a small number of outliers from a set of data observations is always challenging.

no code implementations • 17 Oct 2015 • Victor Amelkin, Ambuj Singh, Petko Bogdanov

In this work, we introduce Social Network Distance (SND) - a distance measure that quantifies the "cost" of evolution of one snapshot of a social network into another snapshot under various models of polar opinion propagation.

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