Lav R. Varshney
About
In The Last Decade
Lav R. Varshney
189 papers receiving 3.5k citations
Hit Papers
Peers
Comparison fields: 5 of 168
- Electrical and Electronic Engineering 1.8k
- Computer Networks and Communications 645
- Artificial Intelligence 563
- Cognitive Neuroscience 373
- Molecular Biology 218
Countries citing papers authored by Lav R. Varshney
This map shows the geographic impact of Lav R. Varshney's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Lav R. Varshney with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lav R. Varshney more than expected).
Fields of papers citing papers by Lav R. Varshney
This network shows the impact of papers produced by Lav R. Varshney. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Lav R. Varshney. The network helps show where Lav R. Varshney may publish in the future.
Co-authorship network of co-authors of Lav R. Varshney
This figure shows the co-authorship network connecting the top 25 collaborators of Lav R. Varshney. A scholar is included among the top collaborators of Lav R. Varshney based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Lav R. Varshney. Lav R. Varshney is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 12 | |
| 5 | MIROSTAT: A NEURAL TEXT DECODING ALGORITHM THAT DIRECTLY CONTROLS PERPLEXITY | 0 |
| 6 | Limits Theorems for Creativity with Intentionality. | 2 |
| 7 | 5 | |
| 8 | 3 | |
| 9 | 1 | |
| 10 | 1 | |
| 11 | Towards Deep Interpretability (MUS-ROVER II): Learning Hierarchical Representations of Tonal Music | 2 |
| 12 | Communication over a Channel that Wears Out | 1 |
| 13 | Sukiyaki in French style: A novel system for transformation of dietary patterns. | 2 |
| 14 | 8 | |
| 15 | 3 | |
| 16 | Clustering-based Phonetic Projection in Mismatched Crowdsourcing Channels for Low-resourced ASR. | 0 |
| 17 | 8 | |
| 18 | To Crowdsource or Not To Crowdsource | 15 |
| 19 | Neural Reconstruction with Approximate Message Passing (NeuRAMP) | 13 |
| 20 | 2 |
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.