Learning a CNN-based End-to-End Controller for a Formula SAE Racecar. - Skanda Koppula (CoRR, 2017)

Applying the Residue Number System to Network Inference. - Mohamed Abdelhamid; Skanda Koppula (CoRR, 2017)

Energy-Efficient Speaker Identification with Low-Precision Networks. - Skanda Koppula; James R. Glass; Anantha P. Chandrakasan (ICASSP, 2018)

Understanding Recurrent Neural State Using Memory Signatures. - Skanda Koppula; Khe Chai Sim; Kean K. Chin (ICASSP, 2018)

SMASH: Co-designing Software Compression and Hardware-Accelerated Indexing for Efficient Sparse Matrix Operations. - Konstantinos Kanellopoulos; Nandita Vijaykumar; Christina Giannoula; Roknoddin Azizi; Skanda Koppula; Nika Mansouri-Ghiasi; Taha Shahroodi; Juan Gómez-Luna; Onur Mutlu (MICRO, 2019)

EDEN: Enabling Energy-Efficient, High-Performance Deep Neural Network Inference Using Approximate DRAM. - Skanda Koppula; Lois Orosa 001; Abdullah Giray Yaglikçi; Roknoddin Azizi; Taha Shahroodi; Konstantinos Kanellopoulos; Onur Mutlu (MICRO, 2019)

Accurate, Low-Latency Visual Perception for Autonomous Racing: Challenges, Mechanisms, and Practical Solutions. - Kieran Strobel; Sibo Zhu; Raphael Chang; Skanda Koppula (IROS, 2020)

Efficient Visual Pretraining with Contrastive Detection. - Olivier J. Hénaff; Skanda Koppula; Jean-Baptiste Alayrac; Aäron van den Oord; Oriol Vinyals; João Carreira 001 (ICCV, 2021)

A Deep Learning Approach for Characterizing Major Galaxy Mergers. - Skanda Koppula; Victor Bapst; Marc Huertas-Company; Sam Blackwell; Agnieszka Grabska-Barwinska; Sander Dieleman; Andrea Huber; Natasha Antropova; Mikolaj Binkowski; Hannah Openshaw; Adrià Recasens; Fernando Caro; et al. (CoRR, 2021)

Object Discovery and Representation Networks. - Olivier J. Hénaff; Skanda Koppula; Evan Shelhamer; Daniel Zoran; Andrew Jaegle; Andrew Zisserman; João Carreira 001; Relja Arandjelovic (ECCV (27), 2022)

Perceiver IO: A General Architecture for Structured Inputs & Outputs. - Andrew Jaegle; Sebastian Borgeaud; Jean-Baptiste Alayrac; Carl Doersch; Catalin Ionescu; David Ding; Skanda Koppula; Daniel Zoran; Andrew Brock; Evan Shelhamer; Olivier J. Hénaff; Matthew M. Botvinick; et al. (ICLR, 2022)

Hierarchical Perceiver. - João Carreira 001; Skanda Koppula; Daniel Zoran; Adrià Recasens; Catalin Ionescu; Olivier J. Hénaff; Evan Shelhamer; Relja Arandjelovic; Matthew M. Botvinick; Oriol Vinyals; Karen Simonyan; Andrew Zisserman; et al. (CoRR, 2022)

Power-Based Side-Channel Attack for AES Key Extraction on the ATMega328 Microcontroller. - Utsav Banerjee; Lisa Ho; Skanda Koppula (CoRR, 2022)

Where Should I Spend My FLOPS? Efficiency Evaluations of Visual Pre-training Methods. - Skanda Koppula; Yazhe Li; Evan Shelhamer; Andrew Jaegle; Nikhil Parthasarathy; Relja Arandjelovic; João Carreira 001; Olivier J. Hénaff (CoRR, 2022)

Lossless Adaptation of Pretrained Vision Models For Robotic Manipulation. - Mohit Sharma 001; Claudio Fantacci; Yuxiang Zhou; Skanda Koppula; Nicolas Heess; Jon Scholz; Yusuf Aytar (ICLR, 2023)

Perception Test: A Diagnostic Benchmark for Multimodal Video Models. - Viorica Patraucean; Lucas Smaira; Ankush Gupta 001; Adrià Recasens; Larisa Markeeva; Dylan Banarse; Skanda Koppula; Joseph Heyward; Mateusz Malinowski; Yi Yang 007; Carl Doersch; Tatiana Matejovicova; et al. (NeurIPS, 2023)

BootsTAP: Bootstrapped Training for Tracking-Any-Point. - Carl Doersch; Pauline Luc; Yi Yang 007; Dilara Gokay; Skanda Koppula; Ankush Gupta 001; Joseph Heyward; Ignacio Rocco; Ross Goroshin; João Carreira 001; Andrew Zisserman (ACCV (2), 2024)

A Simple Recipe for Contrastively Pre-Training Video-First Encoders Beyond 16 Frames. - Pinelopi Papalampidi; Skanda Koppula; Shreya Pathak; Justin Chiu; Joe Heyward; Viorica Patraucean; Jiajun Shen; Antoine Miech; Andrew Zisserman; Aida Nematzadeh (CVPR, 2024)

Memory Consolidation Enables Long-Context Video Understanding. - Ivana Balazevic; Yuge Shi; Pinelopi Papalampidi; Rahma Chaabouni 001; Skanda Koppula; Olivier J. Hénaff (ICML, 2024)

TAPVid-3D: A Benchmark for Tracking Any Point in 3D. - Skanda Koppula; Ignacio Rocco; Yi Yang 007; Joseph Heyward; João Carreira 001; Andrew Zisserman; Gabriel Brostow; Carl Doersch (NeurIPS, 2024)

PaliGemma: A versatile 3B VLM for transfer. - Lucas Beyer; Andreas Steiner 001; André Susano Pinto; Alexander Kolesnikov 003; Xiao Wang 038; Daniel Salz; Maxim Neumann; Ibrahim Alabdulmohsin; Michael Tschannen; Emanuele Bugliarello; Thomas Unterthiner; Daniel Keysers; et al. (CoRR, 2024)

Scaling 4D Representations. - João Carreira 001; Dilara Gokay; Michael King; Chuhan Zhang; Ignacio Rocco; Aravindh Mahendran; Thomas Keck; Joseph Heyward; Skanda Koppula; Etienne Pot; Goker Erdogan; Yana Hasson; et al. (CoRR, 2024)

EcoFlow: Efficient Convolutional Dataflows on Low-Power Neural Network Accelerators. - Lois Orosa 001; Skanda Koppula; Yaman Umuroglu; Konstantinos Kanellopoulos; Juan Gómez-Luna; Michaela Blott; Kees A. Vissers; Onur Mutlu (IEEE Trans. Computers, 2024)

TAPNext: Tracking Any Point (TAP) as Next Token Prediction. - Artem Zholus; Carl Doersch; Yi Yang 007; Skanda Koppula; Viorica Patraucean; Xu Owen He; Ignacio Rocco; Mehdi S. M. Sajjadi; Sarath Chandar; Ross Goroshin (CoRR, 2025)

SciVid: Cross-Domain Evaluation of Video Models in Scientific Applications. - Yana Hasson; Pauline Luc; Liliane Momeni; Maks Ovsjanikov; Guillaume Le Moing; Alina Kuznetsova; Ira Ktena; Jennifer J. Sun; Skanda Koppula; Dilara Gokay; Joseph Heyward; Etienne Pot; et al. (CoRR, 2025)