Vineet Padmanabhan

Vineet Padmanabhan

University of Hyderabad

H-index: 19

Asia-India

About Vineet Padmanabhan

Vineet Padmanabhan, With an exceptional h-index of 19 and a recent h-index of 14 (since 2020), a distinguished researcher at University of Hyderabad, specializes in the field of Artificial Intelligence.

His recent articles reflect a diverse array of research interests and contributions to the field:

Re-examining Class Selectivity in Deep Convolutional Networks

School of Computer and Information Sciences, University of Hyderabad, Prof CR Rao Road, Gachibowli, Hyderabad 500046, India {badola, vineetnair, rajendraprasd}@ uohyd. ac. in

Decomposing the deep: finding class-specific filters in deep CNNs

GPU accelerated matrix factorization of large scale data using block based approach

Content Based Network Representational Learning for Movie Recommendation (CNMovieRec)

Inductive conformal recommender system

A hinge-loss based codebook transfer for cross-domain recommendation with non-overlapping data

Transfer of codebook latent factors for cross-domain recommendation with non-overlapping data

Vineet Padmanabhan Information

University

Position

Professor of Computer Science

Citations(all)

1030

Citations(since 2020)

564

Cited By

859

hIndex(all)

19

hIndex(since 2020)

14

i10Index(all)

35

i10Index(since 2020)

19

Email

University Profile Page

University of Hyderabad

Google Scholar

View Google Scholar Profile

Vineet Padmanabhan Skills & Research Interests

Artificial Intelligence

Top articles of Vineet Padmanabhan

Title

Journal

Author(s)

Publication Date

Re-examining Class Selectivity in Deep Convolutional Networks

Akshay Badola

Vineet Padmanabhan

Rajendra Prasad Lal

2023/6/24

School of Computer and Information Sciences, University of Hyderabad, Prof CR Rao Road, Gachibowli, Hyderabad 500046, India {badola, vineetnair, rajendraprasd}@ uohyd. ac. in

Multi-disciplinary Trends in Artificial Intelligence: 16th International Conference, MIWAI 2023, Hyderabad, India, July 21–22, 2023, Proceedings

Akshay Badola

Vineet Padmanabhan

Rajendra Prasad Lal

2023/7/25

Decomposing the deep: finding class-specific filters in deep CNNs

Neural Computing and Applications

Akshay Badola

Cherian Roy

Vineet Padmanabhan

Rajendra Prasad Lal

2023/6

GPU accelerated matrix factorization of large scale data using block based approach

arXiv preprint arXiv:2304.13724

Prasad Bhavana

Vineet Padmanabhan

2023/1/2

Content Based Network Representational Learning for Movie Recommendation (CNMovieRec)

Nageswar Rao Kota

Vineet Padmanabhan

Wilson Naik Bhukya

2023/6/24

Inductive conformal recommender system

Knowledge-Based Systems

Venkateswara Rao Kagita

Arun K Pujari

Vineet Padmanabhan

Vikas Kumar

2022/8/17

A hinge-loss based codebook transfer for cross-domain recommendation with non-overlapping data

Information Systems

Sowmini Devi Veeramachaneni

Arun K Pujari

Vineet Padmanabhan

Vikas Kumar

2022/7/1

Transfer of codebook latent factors for cross-domain recommendation with non-overlapping data

arXiv preprint arXiv:2203.13995

Sowmini Devi Veeramachaneni

Arun K Pujari

Vineet Padmanabhan

Vikas Kumar

2022/3/26

Systematic Monotonicity and Consistency for Adversarial Natural Language Inference

Brahmani Nutakki

Akshay Badola

Vineet Padmanabhan

2022/12/3

Committee selection using attribute approvals

Venkateswara Rao Kagita

Arun K Pujari

Vineet Padmanabhan

Haris Aziz

Vikas Kumar

2021/5/3

Identifying class specific filters with l1 norm frequency histograms in deep cnns

arXiv preprint arXiv:2112.07719

Akshay Badola

Cherian Roy

Vineet Padmanabhan

Rajendra Lal

2021/12

Matrix factorization of large scale data using multistage matrix factorization

Applied Intelligence

Prasad Bhavana

Vineet Padmanabhan

2021/6

See List of Professors in Vineet Padmanabhan University(University of Hyderabad)