Aditya Grover

Permutation Invariant Graph Generation via Score-Based Generative Modeling

2020 · arXiv (Cornell University)

Learning generative models for graph-structured data is challenging because graphs are discrete, combinatorial, and the underlying data distribution is invariant to the ordering of nodes. However, most of the existing generative models for graphs are …

PiRank: Learning To Rank via Differentiable Sorting.

2020 · arXiv (Cornell University)

A key challenge with machine learning approaches for ranking is the gap between the performance metrics of interest and the surrogate loss functions that can be optimized with gradient-based methods. This gap arises because ranking …

Mamba-ND: Selective State Space Modeling for Multi-Dimensional Data

2024 · arXiv (Cornell University)

In recent years, Transformers have become the de-facto architecture for sequence modeling on text and a variety of multi-dimensional data, such as images and video. However, the use of self-attention layers in a Transformer incurs …