How You See Me. - Rohit Gandikota; Deepak Mishra 002 (CoRR, 2018)

The Child Prodigies of IEEE 802.11 Family. - Rohit Gandikota (CoRR, 2018)

Computer Vision for Autonomous Vehicles. - Rohit Gandikota (CoRR, 2018)

Hiding Audio in Images: A Deep Learning Approach. - Rohit Gandikota; Deepak Mishra 002 (PReMI (2), 2019)

How You See Me: Understanding Convolutional Neural Networks. - Rohit Gandikota; Deepak Mishra 002 (TENCON, 2019)

RTC-GAN: REAL-TIME CLASSIFICATION OF SATELLITE IMAGERY USING DEEP GENERATIVE ADVERSARIAL NETWORKS WITH INFUSED SPECTRAL INFORMATION. - Rohit Gandikota; Radha Krishna K; Anupama Sharma; ManjuSarma M; Vinod M. Bothale (IGARSS, 2020)

Pro-DDPM: Progressive Growing of Variable Denoising Diffusion Probabilistic Models for Faster Convergence. - Rohit Gandikota; Nicholas Brown (BMVC, 2022)

HD-VAE-GAN: Hiding Data with Variational Autoencoder Generative Adversarial Networks. - Rohit Gandikota; Deepak Mishra 002 (CVIP (1), 2022)

Share-GAN: A Novel Shared Task Training in Generative Adversarial Networks for Data Hiding. - Rohit Gandikota; Deepak Mishra 002 (CVIP (1), 2022)

Hiding Video in Images: Harnessing Adversarial Learning on Deep 3D-Spatio-Temporal Convolutional Neural Networks. - Rohit Gandikota; Deepak Mishra 002; Nik Bear Brown (CVIP (1), 2022)

Dismon-Gan: 24×7 All-Weather Optical Domain Surveillance Using Progressively Growing Adversarial Networks with Patch Discriminator. - Rohit Gandikota; Deepak Mishra 002 (IGARSS, 2022)

Pixel Noise Localization Algorithm for Indian Satellite Data Quality Control: A Novel Approach. - Rohit Gandikota; ManjuSarma M (IGARSS, 2022)

Erasing Concepts from Diffusion Models. - Rohit Gandikota; Joanna Materzynska; Jaden Fiotto-Kaufman; David Bau (ICCV, 2023)

Concept Sliders: LoRA Adaptors for Precise Control in Diffusion Models. - Rohit Gandikota; Joanna Materzynska; Tingrui Zhou; Antonio Torralba 001; David Bau (ECCV (40), 2024)

Unified Concept Editing in Diffusion Models. - Rohit Gandikota; Hadas Orgad; Yonatan Belinkov; Joanna Materzynska; David Bau (WACV, 2024)

Erasing Conceptual Knowledge from Language Models. - Rohit Gandikota; Sheridan Feucht; Samuel Marks; David Bau (CoRR, 2024)

Art-Free Generative Models: Art Creation Without Graphic Art Knowledge. - Hui Ren; Joanna Materzynska; Rohit Gandikota; David Bau; Antonio Torralba 001 (CoRR, 2024)

Model Tampering Attacks Enable More Rigorous Evaluations of LLM Capabilities. - Zora Che; Stephen Casper; Robert Kirk; Anirudh Satheesh; Stewart Slocum; Lev E. McKinney; Rohit Gandikota; Aidan Ewart; Domenic Rosati; Zichu Wu; Zikui Cai; Bilal Chughtai; et al. (Trans. Mach. Learn. Res., 2025)

SliderSpace: Decomposing the Visual Capabilities of Diffusion Models. - Rohit Gandikota; Zongze Wu 002; Richard Zhang 001; David Bau; Eli Shechtman; Nicholas I. Kolkin (CoRR, 2025)

Distilling Diversity and Control in Diffusion Models. - Rohit Gandikota; David Bau (CoRR, 2025)

When Are Concepts Erased From Diffusion Models? - Kevin Lu; Nicky Kriplani; Rohit Gandikota; Minh Pham 005; David Bau; Chinmay Hegde; Niv Cohen (CoRR, 2025)

Discovering Forbidden Topics in Language Models. - Can Rager; Chris Wendler; Rohit Gandikota; David Bau (CoRR, 2025)