Akash Srivastava
24 papers · 2017–2026 · 5 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
Jump to papers ↓+7 more ↓ Show less ↑
πΊοΈ Taxonomy Completionist (51) π Academic Marathon Β· Sprint π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
π§
Keyword Pioneer
ποΈ
Keyword Collector
(122)
π
Trend Setter
π
Renaissance Researcher
(7)
π₯
Unstoppable Β· Silver
β‘
Prolific Year Β· Productive
π
Century Club Β· Bronze
Top co-authors
Research topics
Machine Learning
(17)
Deep Learning
(15)
Artificial Intelligence
(10)
Optimization & Theory
(10)
Models
(9)
Core AI
(7)
Learning Types Β· Machine Learning
(7)
Learning Types Β· Deep Learning
(5)
Bayesian & Probabilistic
(4)
Interdisciplinary
(3)
Architectures
(3)
Computer Vision
(2)
Healthcare & Medicine
(2)
Natural Language Processing
(2)
Application Areas
(2)
Keywords
neural network
(4)
variational inference
(4)
variational autoencoder
(3)
large language model
(3)
diffusion model
(3)
representation learning
(3)
contrastive learning
(3)
image generation
(2)
uncertainty quantification
(2)
extracellular recordings
(2)
transfer learning
(2)
spike sorting
(2)
generative model
(2)
neural dynamics
(1)
reinforcement learning
(1)
probabilistic modeling
(1)
causal inference
(1)
offline reinforcement learning
(1)
bayesian nonparametrics
(1)
image classification
(1)
Papers
DICE: Discrete Inversion Enabling Controllable Editing for Masked Generative Models
WACV 2026
Hopscotch: Discovering and Skipping Redundancies in Language Models
EMNLP 2025
SODA: Spectral Orthogonal Decomposition Adaptation for Diffusion Models
WACV 2025
Unveiling the Secret Recipe: A Guide For Supervised Fine-Tuning Small LLMs
ICLR 2025
A Probabilistic Framework for Modular Continual Learning
ICLR 2024
Curiosity-driven Red-teaming for Large Language Models
ICLR 2024
ProxEdit: Improving Tuning-Free Real Image Editing With Proximal Guidance
WACV 2024
Aligning Optimization Trajectories with Diffusion Models for Constrained Design Generation
NeurIPS 2023
Analyzing Generalization of Neural Networks through Loss Path Kernels
NeurIPS 2023
Beyond Uniform Sampling: Offline Reinforcement Learning with Imbalanced Datasets
NeurIPS 2023
Compositional Foundation Models for Hierarchical Planning
NeurIPS 2023
Identifiability Guarantees for Causal Disentanglement from Soft Interventions
NeurIPS 2023
Multi-Symmetry Ensembles: Improving Diversity and Generalization via Opposing Symmetries
ICML 2023
Post-processing Private Synthetic Data for Improving Utility on Selected Measures
NeurIPS 2023
Towards robust and generalizable representations of extracellular data using contrastive learning
NeurIPS 2023
Equivariant Self-Supervised Learning: Encouraging Equivariance in Representations
ICLR 2022
A Bayesian-Symbolic Approach to Reasoning and Learning in Intuitive Physics
NeurIPS 2021
Targeted Neural Dynamical Modeling
NeurIPS 2021
Generative Ratio Matching Networks
ICLR 2020
Scalable Spike Source Localization in Extracellular Recordings using Amortized Variational Inference
NeurIPS 2019
Variational Russian Roulette for Deep Bayesian Nonparametrics
ICML 2019
Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam
ICML 2018
HOUDINI: Lifelong Learning as Program Synthesis
NeurIPS 2018
VEEGAN: Reducing Mode Collapse in GANs using Implicit Variational Learning
NeurIPS 2017